Datasets:

KaiWu123
/

awesome-ai4ai

key stringlengths 8 50	title stringlengths 11 130	venue stringlengths 1 111	date stringlengths 4 7	url stringlengths 28 159	arxiv_id stringlengths 0 10	code stringlengths 0 68	citations int64 0 21.3k	github_stars int64 0 64k	collections listlengths 0 3	sections listlengths 1 3
10778628	JARVIS-1: Open-World Multi-Task Agents With Memory-Augmented Multimodal Language Models	IEEE Transactions on Pattern Analysis & Machine Intelligence	2023-11	https://doi.ieeecomputersociety.org/10.1109/TPAMI.2024.3511593	2311.05997	https://github.com/CraftJarvis/JARVIS-1	206	410	[ "harness-design" ]	[ "targets/harness" ]
11334583	LongCodeZip: Compress Long Context for Code Language Models	2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)	2025-10	https://doi.org/10.1109/ase63991.2025.00020	2510.00446	https://github.com/YerbaPage/LongCodeZip	42	164	[ "harness-design" ]	[ "targets/harness" ]
anokhin2025herobench	HeroBench: A Benchmark for Long-Horizon Planning and Structured Reasoning in Virtual Worlds	arXiv preprint arXiv:2508.12782	2025-08	https://arxiv.org/abs/2508.12782	2508.12782	https://github.com/stefanrer/HeroBench	6	14	[ "benchmarks" ]	[ "evidence/benchmarks" ]
bfcl2025	The Berkeley Function Calling Leaderboard (BFCL): From tool use to agentic evaluation of large language models	Proceedings of the 42nd International Conference on Machine Learning	2025	https://proceedings.mlr.press/v267/patil25a.html		https://github.com/ShishirPatil/gorilla	435	13,007	[ "benchmarks" ]	[ "evidence/benchmarks" ]
bonatti2025windows	Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale	International Conference on Machine Learning	2024-09	https://arxiv.org/abs/2409.08264	2409.08264	https://github.com/microsoft/WindowsAgentArena	194	889	[ "benchmarks" ]	[ "evidence/benchmarks" ]
buildbench2025	BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software	arXiv	2025-09	https://arxiv.org/abs/2509.25248	2509.25248		1	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
cai2026mossselfevolutionsourcelevelrewriting	MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems	arXiv	2026-05	https://arxiv.org/abs/2605.22794	2605.22794	https://github.com/hkgai-official/Moss	5	21	[ "harness-design" ]	[ "targets/harness" ]
cemri2026multi	Why Do Multi-Agent LLM Systems Fail?	Advances in Neural Information Processing Systems	2025-03	https://proceedings.neurips.cc/paper_files/paper/2025/hash/b1041e52d3be19f0a9bc491657488e4a-Abstract-Datasets_and_Benchmarks_Track.html	2503.13657	https://github.com/multi-agent-systems-failure-taxonomy/MAST	535	410	[ "benchmarks", "harness-design" ]	[ "evidence/benchmarks", "targets/harness" ]
chan2025mlebench	MLE-bench: Evaluating machine learning agents on machine learning engineering	ICLR 2025	2024-10	https://arxiv.org/abs/2410.07095	2410.07095	https://github.com/openai/mle-bench	360	1,716	[ "benchmarks" ]	[ "evidence/benchmarks" ]
chen2024spin	SPIN: Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models	Proceedings of the 41st International Conference on Machine Learning	2024	https://proceedings.mlr.press/v235/chen24j.html		https://github.com/uclaml/SPIN	621	1,254	[]	[ "targets/weights" ]
chen2025iterresearch	IterResearch: Rethinking Long-Horizon Agents with Interaction Scaling	arXiv preprint arXiv:2511.07327	2025-11	https://arxiv.org/abs/2511.07327	2511.07327	https://github.com/Alibaba-NLP/DeepResearch	17	19,873	[ "model-design" ]	[ "targets/weights" ]
chen2025loop	Reinforcement Learning for Long-Horizon Interactive LLM Agents	arXiv preprint arXiv:2502.01600	2025-02	https://arxiv.org/abs/2502.01600	2502.01600		99	0	[ "model-design" ]	[ "targets/weights" ]
chen2025mlrbench	MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research	arXiv preprint arXiv:2505.19955	2025-05	https://arxiv.org/abs/2505.19955	2505.19955	https://github.com/chchenhui/mlrbench	49	34	[ "benchmarks" ]	[ "evidence/benchmarks" ]
chen2026agent	Agent^2 RL-Bench: Can LLM Agents Engineer Agentic RL Post-Training?	arXiv preprint arXiv:2604.10547	2026-04	https://arxiv.org/abs/2604.10547	2604.10547	https://github.com/microsoft/RD-Agent	3	14,332	[ "benchmarks" ]	[ "evidence/benchmarks" ]
chen2026aiscientist	Toward autonomous long-horizon engineering for ML research	arXiv	2026-04	https://arxiv.org/abs/2604.13018	2604.13018	https://github.com/AweAI-Team/AiScientist	8	145	[ "benchmarks", "harness-design" ]	[ "targets/substrate" ]
chen2026harnessxcomposableadaptiveevolvable	HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry	arXiv	2026-06	https://arxiv.org/abs/2606.14249	2606.14249		15	0	[ "harness-design" ]	[ "targets/harness" ]
chen2026knowu	KnowU-Bench: Towards Interactive, Proactive, and Personalized Mobile Agent Evaluation	arXiv preprint arXiv:2604.08455	2026-04	https://arxiv.org/abs/2604.08455	2604.08455	https://github.com/ZJU-REAL/KnowU-Bench	16	75	[ "benchmarks" ]	[ "evidence/benchmarks" ]
chen2026pastprologueplugincontroller	The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory	arXiv	2026-06	https://arxiv.org/abs/2606.31121	2606.31121		1	0	[ "harness-design" ]	[ "targets/harness" ]
chen2026recursiveselfimprovementaibounded	Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops	—	2026-07	https://arxiv.org/abs/2607.07663	2607.07663		6	0	[ "harness-design" ]	[ "analyses" ]
chhikara2025mem0	Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory	European Conference on Artificial Intelligence (ECAI)	2025-04	https://doi.org/10.3233/faia251160	2504.19413	https://github.com/mem0ai/mem0	567	64,001	[ "harness-design" ]	[ "targets/harness" ]
choudhury2025processrewardmodelsllm	Process Reward Models for LLM Agents: Practical Framework and Directions	arXiv	2025-02	https://arxiv.org/abs/2502.10325	2502.10325	https://github.com/sanjibanc/agent_prm	79	59	[ "harness-design" ]	[ "targets/harness" ]
cirepairbench2026	CI-Repair-Bench: A Repository-Aware Benchmark for Automated Patch Validation via CI Workflows	arXiv	2026-04	https://arxiv.org/abs/2604.27148	2604.27148	https://github.com/RabeyaMuna/CI-REPAIR-BENCH	0	1	[ "benchmarks" ]	[ "evidence/benchmarks" ]
clitoolbench2026	Evaluating LLM-Based 0-to-1 Software Generation in End-to-End CLI Tool Scenarios	arXiv	2026-04	https://arxiv.org/abs/2604.06742	2604.06742	https://github.com/kinesiatricssxilm14/CLI-Tool-Bench	1	2	[ "benchmarks" ]	[ "evidence/benchmarks" ]
dataenvgym2025	DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback	International Conference on Learning Representations	2024-10	https://arxiv.org/abs/2410.06215	2410.06215	https://github.com/codezakh/DataEnvGym	20	34	[]	[ "targets/data" ]
deepswe2026	DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks	arXiv preprint arXiv:2607.07946	2026-07	https://arxiv.org/abs/2607.07946	2607.07946	https://github.com/datacurve-ai/deep-swe	13	1,488	[ "benchmarks" ]	[ "evidence/benchmarks" ]
deng2023mind2web	Mind2Web: Towards a Generalist Agent for the Web	Advances in Neural Information Processing Systems	2023-06	https://arxiv.org/abs/2306.06070	2306.06070	https://github.com/OSU-NLP-Group/Mind2Web	1,370	1,021	[ "benchmarks" ]	[ "evidence/benchmarks" ]
deng2026swemilestone	SWE-Milestone: Evaluating AI Agents on Continuous Software Evolution	International Conference on Machine Learning	2026-03	https://arxiv.org/abs/2603.13428	2603.13428	https://github.com/DeepCommit-ai/SWE-Milestone	6	70	[ "benchmarks" ]	[ "evidence/benchmarks" ]
dong2026longhorizon	Towards Long-Horizon Agents: A Survey	Preprints	2026	https://doi.org/10.20944/preprints202607.1328.v1			0	0	[]	[ "analyses" ]
du2025deepresearch	DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents	arXiv preprint arXiv:2506.11763	2025-06	https://arxiv.org/abs/2506.11763	2506.11763	https://github.com/Ayanami0730/deep_research_bench	212	816	[ "benchmarks" ]	[ "evidence/benchmarks" ]
erdogan2025planandact	Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks	International Conference on Machine Learning	2025-03	https://arxiv.org/abs/2503.09572	2503.09572	https://github.com/SqueezeAILab/plan-and-act	197	45	[ "model-design" ]	[ "targets/weights" ]
fang-etal-2026-memp	Memp: Exploring Agent Procedural Memory	Findings of the Association for Computational Linguistics: ACL 2026	2025-08	https://aclanthology.org/2026.findings-acl.866/	2508.06433	https://github.com/zjunlp/MemP	62	35	[ "harness-design" ]	[ "targets/harness" ]
featurebench2026	FeatureBench: Benchmarking Agentic Coding for Complex Feature Development	arXiv	2026-02	https://arxiv.org/abs/2602.10975	2602.10975	https://github.com/LiberCoders/FeatureBench	26	87	[ "benchmarks" ]	[ "evidence/benchmarks" ]
feng2025gigpo	Group-in-Group Policy Optimization for LLM Agent Training	Advances in Neural Information Processing Systems	2025-05	https://arxiv.org/abs/2505.10978	2505.10978	https://github.com/langfengQ/verl-agent	375	2,250	[ "model-design" ]	[ "targets/weights" ]
frontierswe2026	FrontierSWE	Proximal Blog	2026	https://frontierswe.com/blog		https://github.com/Proximal-Labs/frontier-swe	0	219	[ "benchmarks" ]	[ "evidence/benchmarks" ]
gaosurvey	A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence	TMLR 2026	2025-07	https://arxiv.org/abs/2507.21046	2507.21046	https://github.com/CharlesQ9/Self-Evolving-Agents	99	1,300	[]	[ "analyses" ]
gonzalezpumariega2025robotouille	Robotouille: An Asynchronous Planning Benchmark for LLM Agents	International Conference on Learning Representations	2025-02	https://arxiv.org/abs/2502.05227	2502.05227	https://github.com/portal-cornell/robotouille	37	46	[ "benchmarks" ]	[ "evidence/benchmarks" ]
gou2024critic	CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing	International Conference on Learning Representations	2023-05	https://arxiv.org/abs/2305.11738	2305.11738	https://github.com/microsoft/ProphetNet	863	746	[ "harness-design" ]	[ "targets/harness" ]
gou2025mind2web	Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge	arXiv preprint arXiv:2506.21506	2025-06	https://arxiv.org/abs/2506.21506	2506.21506	https://github.com/OSU-NLP-Group/Mind2Web-2	68	114	[ "benchmarks" ]	[ "evidence/benchmarks" ]
gulati2026askearlyasklate	Ask Early, Ask Late, Ask Right: When Does Clarification Timing Matter for Long-Horizon Agents?	arXiv	2026-05	https://arxiv.org/abs/2605.07937	2605.07937		2	0	[ "harness-design" ]	[ "targets/harness" ]
guo2026questionansweringtaskcompletion	From Question Answering to Task Completion: A Survey on Agent System and Harness Design	arXiv	2026-06	https://arxiv.org/abs/2606.20683	2606.20683		3	0	[ "harness-design" ]	[ "targets/harness" ]
gutierrez2024hipporag	HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models	Advances in Neural Information Processing Systems	2024-05	https://arxiv.org/abs/2405.14831	2405.14831	https://github.com/OSU-NLP-Group/HippoRAG	328	3,963	[ "harness-design" ]	[ "targets/harness" ]
han2026robocerebra	RoboCerebra: A Large-scale Benchmark for Long-horizon Robotic Manipulation Evaluation	Advances in Neural Information Processing Systems	2025-06	https://arxiv.org/abs/2506.06677	2506.06677	https://github.com/buaa-colalab/RoboCerebra	30	75	[ "benchmarks" ]	[ "evidence/benchmarks" ]
he2024webvoyager	WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models	Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)	2024-01	https://arxiv.org/abs/2401.13919	2401.13919	https://github.com/MinorJerry/WebVoyager	434	1,122	[ "benchmarks" ]	[ "evidence/benchmarks" ]
hill2023mineplanner	MinePlanner: A Benchmark for Long-Horizon Planning in Large Minecraft Worlds	Proceedings of the 6th ICAPS Workshop on the International Planning Competition (WIPC)	2023-12	https://arxiv.org/abs/2312.12891	2312.12891	https://github.com/IretonLiu/mine-pddl	8	23	[ "benchmarks" ]	[ "evidence/benchmarks" ]
hou2026single	Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning	arXiv preprint arXiv:2607.07508	2026-07	https://arxiv.org/abs/2607.07508	2607.07508		7	0	[ "model-design" ]	[ "targets/weights" ]
hu2025adas	Automated design of agentic systems	ICLR 2025	2024-08	https://arxiv.org/abs/2408.08435	2408.08435	https://github.com/ShengranHu/ADAS	282	1,631	[ "harness-design" ]	[ "targets/harness" ]
hu2025memory	Memory in the Age of AI Agents	arXiv preprint arXiv:2512.13564	2025-12	https://arxiv.org/abs/2512.13564	2512.13564		245	0	[ "harness-design" ]	[ "targets/harness" ]
hu2025step	Step-DeepResearch Technical Report	arXiv preprint arXiv:2512.20491	2025-12	https://arxiv.org/abs/2512.20491	2512.20491	https://github.com/stepfun-ai/StepDeepResearch	12	571	[ "harness-design" ]	[ "targets/harness" ]
huang2024selfcorrect	Large Language Models Cannot Self-Correct Reasoning Yet	International Conference on Learning Representations	2023-10	https://arxiv.org/abs/2310.01798	2310.01798		1,135	0	[ "harness-design" ]	[ "targets/harness" ]
huang2026rawexperienceskillconsumption	From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills	arXiv	2026-05	https://arxiv.org/abs/2605.23899	2605.23899		13	0	[ "harness-design" ]	[ "targets/harness" ]
imajuku2025alebench	ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering	Advances in Neural Information Processing Systems	2025-06	https://arxiv.org/abs/2506.09050	2506.09050	https://github.com/SakanaAI/ALE-Bench	28	213	[ "benchmarks" ]	[ "evidence/benchmarks" ]
jansen2025codescientist	CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation	Findings of the Association for Computational Linguistics: ACL 2025	2025	https://aclanthology.org/2025.findings-acl.692/		https://github.com/allenai/codescientist	55	348	[]	[ "targets/substrate" ]
jiang2025aide	AIDE: AI-driven exploration in the space of code	arXiv	2025-02	https://arxiv.org/abs/2502.13138	2502.13138	https://github.com/WecoAI/aideml	174	1,491	[]	[ "targets/data" ]
jiang2026darwindynamicagenticallyrewriting	DARWIN: Dynamic Agentically Rewriting Self-Improving Network	arXiv	2026-02	https://arxiv.org/abs/2602.05848	2602.05848	https://github.com/henryyjiang/DARWIN	1	0	[ "harness-design" ]	[ "targets/harness" ]
jimenez2024swe	SWE-bench: Can Language Models Resolve Real-World GitHub Issues?	ICLR 2024	2023-10	https://arxiv.org/abs/2310.06770	2310.06770	https://github.com/SWE-bench/SWE-bench	3,453	5,705	[ "benchmarks" ]	[ "foundations/long-horizon" ]
jin2026chainswe	ChainSWE: Benchmarking Coding Agents on Multi-Bug Software Maintenance	arXiv preprint arXiv:2607.02606	2026-07	https://arxiv.org/abs/2607.02606	2607.02606		1	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
jin2026reveal	ReVeal: Self-Evolving Code Agents via Reliable Self-Verification	The Fourteenth International Conference on Learning Representations	2025-06	https://arxiv.org/abs/2506.11442	2506.11442		12	0	[ "harness-design" ]	[ "targets/harness" ]
kamoi2024can	When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs	Transactions of the Association for Computational Linguistics	2024-06	https://arxiv.org/abs/2406.01297	2406.01297		327	0	[ "harness-design" ]	[ "targets/harness" ]
kang2025acon	ACON: Optimizing Context Compression for Long-horizon LLM Agents	arXiv preprint arXiv:2510.00615	2025-10	https://arxiv.org/abs/2510.00615	2510.00615	https://github.com/microsoft/acon	84	106	[ "harness-design" ]	[ "targets/harness" ]
kapoor2024omniact	OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web	Computer Vision -- ECCV 2024	2024-02	https://arxiv.org/abs/2402.17553	2402.17553		167	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
kapoor2025holistic	Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation	arXiv preprint arXiv:2510.11977	2025-10	https://arxiv.org/abs/2510.11977	2510.11977	https://github.com/princeton-pli/hal-harness	56	311	[ "benchmarks" ]	[ "evidence/benchmarks" ]
khalifa2026process	Process Reward Models That Think	Transactions on Machine Learning Research	2025-04	https://arxiv.org/abs/2504.16828	2504.16828	https://github.com/mukhal/ThinkPRM	103	91	[ "harness-design" ]	[ "targets/harness" ]
khanal2026beyond	Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents	arXiv preprint arXiv:2603.29231	2026-03	https://arxiv.org/abs/2603.29231	2603.29231		5	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
kim2026sciencescalingagentsystems	Towards a Science of Scaling Agent Systems	arXiv	2025-12	https://arxiv.org/abs/2512.08296	2512.08296	https://github.com/ybkim95/agent-scaling	115	42	[ "benchmarks", "harness-design" ]	[ "evidence/benchmarks", "targets/harness" ]
kimi2026k3	Kimi K3: Open Frontier Intelligence	arXiv	2026-07	https://arxiv.org/abs/2607.24653	2607.24653	https://github.com/MoonshotAI/Kimi-K3	8	8,617	[ "benchmarks", "model-design", "harness-design" ]	[ "evidence/benchmarks", "targets/weights", "targets/harness" ]
kirgis2026shadow	Can AI Agents Conduct Open-Ended AI Research? Early Evidence from Two Case Studies	arXiv	2026-07	https://arxiv.org/abs/2607.27191	2607.27191		3	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
koh2024visualwebarena	VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks	Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)	2024-01	https://arxiv.org/abs/2401.13649	2401.13649	https://github.com/web-arena-x/visualwebarena	0	485	[ "benchmarks" ]	[ "evidence/benchmarks" ]
kovacs2026squeez	Squeez: Task-Conditioned Tool-Output Pruning for Coding Agents	arXiv preprint arXiv:2604.04979	2026-04	https://arxiv.org/abs/2604.04979	2604.04979	https://github.com/KRLabsOrg/squeez	2	23	[ "harness-design" ]	[ "targets/harness" ]
kulikov2026autodata	Autodata: An Agentic Data Scientist to Create High Quality Synthetic Data	arXiv	2026-06	https://arxiv.org/abs/2606.25996	2606.25996		6	0	[ "model-design" ]	[ "targets/data" ]
kwa2026measuring	Measuring AI Ability to Complete Long Software Tasks	NeurIPS 2025	2025-03	https://arxiv.org/abs/2503.14499	2503.14499	https://github.com/METR/eval-analysis-public	134	313	[]	[ "evidence/measurement" ]
laban2026llms	LLMs Get Lost In Multi-Turn Conversation	International Conference on Learning Representations	2025-05	https://arxiv.org/abs/2505.06120	2505.06120	https://github.com/microsoft/lost_in_conversation	398	296	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lange2025shinkaevolve	ShinkaEvolve: Towards open-ended and sample-efficient program evolution	arXiv	2025-09	https://openreview.net/forum?id=lKEdGCoDNC	2509.19349	https://github.com/SakanaAI/ShinkaEvolve	139	1,354	[]	[ "targets/substrate" ]
lee2024benchmarking	Benchmarking Mobile Device Control Agents across Diverse Configurations	arXiv preprint arXiv:2404.16660	2024-04	https://arxiv.org/abs/2404.16660	2404.16660	https://github.com/jylee425/b-moca	47	33	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lee2025learning	Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents	The Thirteenth International Conference on Learning Representations	2025-03	https://arxiv.org/abs/2503.10689	2503.10689	https://github.com/dgjun32/lcow_iclr2025	21	6	[ "harness-design" ]	[ "targets/harness" ]
lee2026metaharness	Meta-Harness: End-to-End Optimization of Model Harnesses	arXiv	2026-03	https://arxiv.org/abs/2603.28052	2603.28052	https://github.com/stanford-iris-lab/meta-harness-tbench2-artifact	141	1,183	[ "harness-design" ]	[ "targets/harness" ]
lee2026rhi	Recursive harness self-improvement	arXiv	2026-07	https://arxiv.org/abs/2607.15524	2607.15524		6	0	[ "harness-design" ]	[ "targets/harness" ]
li2023behavior	BEHAVIOR-1K: A benchmark for embodied AI with 1,000 everyday activities and realistic simulation	Proceedings of The 6th Conference on Robot Learning	2023	https://proceedings.mlr.press/v205/li23a.html		https://github.com/StanfordVL/BEHAVIOR-1K	382	1,657	[ "benchmarks" ]	[ "evidence/benchmarks" ]
li2025salt	SALT: Step-level Advantage Assignment for Long-horizon Agents via Trajectory Graph	Findings of the Association for Computational Linguistics: EACL 2026	2025-10	https://arxiv.org/abs/2510.20022	2510.20022		16	0	[ "model-design" ]	[ "targets/weights" ]
li2025sorl	Stabilizing Off-Policy Training for Long-Horizon LLM Agent via Turn-Level Importance Sampling and Clipping-Triggered Normalization	arXiv preprint arXiv:2511.20718	2025-11	https://arxiv.org/abs/2511.20718	2511.20718	https://github.com/Cloud0723/SORL	4	0	[ "model-design" ]	[ "targets/weights" ]
li2025webweaver	WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research	arXiv preprint arXiv:2509.13312	2025-09	https://arxiv.org/abs/2509.13312	2509.13312	https://github.com/Alibaba-NLP/DeepResearch	41	19,873	[ "harness-design" ]	[ "targets/harness" ]
li2026acmagenticcontextmanagement	ACM: Agentic Context Management for Long Horizon Tasks	arXiv	2026-07	https://arxiv.org/abs/2607.23809	2607.23809	https://github.com/lixiaochuan2020/agentic-context-management	0	31	[ "harness-design" ]	[ "targets/harness" ]
li2026autosota	AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery	arXiv	2026-04	https://arxiv.org/abs/2604.05550	2604.05550	https://github.com/tsinghua-fib-lab/AutoSOTA	15	662	[ "benchmarks" ]	[ "targets/substrate" ]
li2026compactionrlreinforcementlearningcontext	CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents	arXiv	2026-07	https://arxiv.org/abs/2607.05378	2607.05378		1	0	[ "harness-design" ]	[ "targets/harness" ]
li2026harness	Agent Harness Engineering: A Survey	—	2026	https://picrew.github.io/LLM-Harness/		https://github.com/Picrew/LLM-Harness	0	2	[]	[ "analyses" ]
li2026weavebench	WeaveBench: A Long-Horizon, Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces	arXiv preprint arXiv:2606.09426	2026-06	https://arxiv.org/abs/2606.09426	2606.09426		4	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
liao2026kernelevolve	KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta	arXiv	2025-12	https://doi.org/10.1109/ISCA66397.2026.00063	2512.23236		2	0	[]	[ "targets/substrate" ]
lindenbauer2025complexity	The Complexity Trap: Simple Observation Masking Is as Efficient as LLM Summarization for Agent Context Management	arXiv preprint arXiv:2508.21433	2025-08	https://arxiv.org/abs/2508.21433	2508.21433		23	0	[ "harness-design" ]	[ "targets/harness" ]
liu2024agentbench	AgentBench: Evaluating LLMs as Agents	International Conference on Learning Representations	2023-08	https://arxiv.org/abs/2308.03688	2308.03688	https://github.com/THUDM/AgentBench	1,185	3,691	[ "benchmarks" ]	[ "evidence/benchmarks" ]
liu2025mlmaster	ML-Master: Towards AI-for-AI via integration of exploration and reasoning	arXiv	2025-06	https://arxiv.org/abs/2506.16499	2506.16499	https://github.com/sjtu-sai-agents/ML-Master	54	447	[ "benchmarks" ]	[ "targets/data" ]
liu2026diveclaudecodedesign	Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems	arXiv	2026-04	https://arxiv.org/abs/2604.14228	2604.14228	https://github.com/VILA-Lab/Dive-into-Claude-Code	28	2,078	[ "harness-design" ]	[ "targets/harness" ]
liu2026escherloopmutualevolutionclosedloop	Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization	arXiv	2026-04	https://arxiv.org/abs/2604.23472	2604.23472	https://github.com/scaling-group/escher-loop	5	7	[ "harness-design" ]	[ "targets/harness" ]
liu2026llms	Do LLMs Catch Their Own Mistakes? A Comprehensive Benchmark for Reflective Tool Use LLMs	Findings of the Association for Computational Linguistics: ACL 2026	2026	https://aclanthology.org/2026.findings-acl.86/			0	0	[ "benchmarks" ]	[ "evidence/benchmarks" ]
longclibench2026	LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces	arXiv	2026-02	https://arxiv.org/abs/2602.14337	2602.14337	https://github.com/finyorko/longcli-bench	21	46	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lu-etal-2025-runaway	Runaway is Ashamed, But Helpful: On the Early-Exit Behavior of Large Language Model-based Agents in Embodied Environments	Findings of the Association for Computational Linguistics: EMNLP 2025	2025-05	https://aclanthology.org/2025.findings-emnlp.1304/	2505.17616	https://github.com/Coldmist-Lu/AgentExit	7	2	[ "harness-design" ]	[ "targets/harness" ]
lu2024aiscientist	The AI Scientist: Towards fully automated open-ended scientific discovery	arXiv	2024-08	https://arxiv.org/abs/2408.06292	2408.06292	https://github.com/SakanaAI/AI-Scientist	1,059	14,442	[]	[ "targets/research" ]
lu2026endtoendautomation	Towards End-to-End Automation of AI Research	Nature 2026	2026-03	https://doi.org/10.1038/s41586-026-10265-5		https://github.com/SakanaAI/AI-Scientist-v2	211	7,048	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lu2026meta	The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?	arXiv preprint arXiv:2606.04455	2026-06	https://arxiv.org/abs/2606.04455	2606.04455	https://github.com/ant-research/meta-agent-challenge	2	20	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lu2402weblinx	WebLINX: Real-World Website Navigation with Multi-Turn Dialogue	International Conference on Machine Learning	2024-02	https://arxiv.org/abs/2402.05930	2402.05930	https://github.com/McGill-NLP/weblinx	182	163	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lu2408toolsandbox	ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities	Findings of the Association for Computational Linguistics: NAACL 2025	2024-08	https://aclanthology.org/2025.findings-naacl.65/	2408.04682	https://github.com/apple/ToolSandbox	221	279	[ "benchmarks" ]	[ "evidence/benchmarks" ]
lupidi2026airsbench	AIRS-Bench: A Suite of Tasks for Frontier AI Research Science Agents	arXiv	2026-02	https://arxiv.org/abs/2602.06855	2602.06855	https://github.com/facebookresearch/airs-bench	19	111	[ "benchmarks" ]	[ "evidence/benchmarks" ]

End of preview. Expand in Data Studio

Awesome AI4AI — the catalog behind the survey

The structured catalog accompanying "AI4AI Survey: From Long-Horizon Agents to Recursive Self-Improvement — Definitions, Reliable Horizons, and Open Problems", by 23 authors across TJU, SJTU, UC Berkeley, UCAS, NUS, NTU, and Simple Agent Lab.

📄 Paper: https://www.preprints.org/manuscript/202608.2108/v1
🔗 DOI: https://doi.org/10.5281/zenodo.22198847
📥 PDF, original layout: https://raw.githubusercontent.com/KaiWU5/Awesome-AI4AI/main/assets/AI4AI-Survey.pdf
🌐 Project site: https://kaiwu5.github.io/Awesome-AI4AI/
⭐ Repo (updated weekly): https://github.com/KaiWU5/Awesome-AI4AI
🔧 Harness: https://github.com/simple-agent-lab/RSIHub

What this is

"Can AI improve AI" is asserted constantly and measured rarely. The literature is fragmented: long-horizon agents, AI4AI, self-improvement, and recursive self-improvement are four largely separate conversations that don't reliably cite each other, so it is genuinely hard to tell how much progress is real.

We read 223 papers and organized them around one question:

How far can an AI system reliably carry an improvement process from idea to verified result?

That reframing forces you to say what is being improved — data, weights, the harness, the evaluator, or the research process itself — and, critically, who supplies each part of the loop.

Finding 1: AI does the work; humans still set the bar

Today's systems are increasingly excellent at the work of improvement: planning, writing code, running experiments, optimizing, repairing. But humans still overwhelmingly determine the goals, the evaluation criteria, and what counts as progress. The part that got automated and the part that decides whether the automation was worth running are not the same part.

Finding 2: The composition gap

Strong performance on individual components rarely translates into reliable end-to-end improvement. A system can beat every component benchmark and still fail the full idea→verified-result loop. A lot of "self-improving AI" claims are really component claims being extrapolated across a gap the evidence doesn't cover.

On evidence standards

We separate demonstrated capability from extrapolated autonomy. For an intervention to count as extending the reliable horizon, the evaluation has to actually attribute a boundary shift — matched evaluation, not a number rising on a benchmark whose contamination status is unclear. By that standard, evidence for reliable research judgment, causal experimentation, persistent gains, and compounding improvement is thinner than the discourse suggests.

Collection	Papers
Benchmarks	111
Harness design	98
Model design	26
Total public papers	223

225 have arXiv IDs; 166 link to code. Citations, GitHub stars, and rankings are refreshed weekly in the source repository.

Schema

One JSON object per line in papers.jsonl:

field	type	description
`key`	string	citation key from the survey bibliography
`title`	string	paper title
`venue`	string	publication venue
`date`	string	`YYYY-MM`
`url`	string	canonical link (DOI or publisher)
`arxiv_id`	string	arXiv ID where one exists
`code`	string	code repository where one exists
`citations`	int	citation count at last refresh
`github_stars`	int	stars at last refresh
`collections`	list[string]	`benchmarks`, `harness-design`, `model-design`
`sections`	list[string]	survey section(s) citing the paper

Usage

from datasets import load_dataset
ds = load_dataset("awesome-ai4ai", split="train")

# every benchmark paper that ships code
benches = ds.filter(lambda r: "benchmarks" in r["collections"] and r["code"])
print(len(benches))

Citation

@techreport{{ai4ai2026survey,
  title  = {{{{AI4AI}} Survey: From Long-Horizon Agents to Recursive Self-Improvement---Definitions, Reliable Horizons, and Open Problems}},
  author = {{Wu, Kai and Lyu, Hao and Luo, Zhen and others}},
  year   = {{2026}},
  howpublished = {{Preprints.org}},
  doi    = {{10.5281/zenodo.22198847}},
  url    = {{https://doi.org/10.5281/zenodo.22198847}}
}}