Point dataset card to TIGER-Lab/ClawBench Space + add What's New section + sync V2 trace ref to TIGER-Lab mirror

README.md

@@ -31,25 +31,29 @@ configs:
         path: data/train-00000-of-00001.parquet
 arxiv: "2604.08523"
 viewer: true
-leaderboard: NAIL-Group/clawbench-leaderboard
+leaderboard: TIGER-Lab/ClawBench
 ---
 
-# ClawBench — A Benchmark for AI Web Agents
+# ClawBench Dataset
 
-**Can AI Agents Complete Everyday Online Tasks?**
+ClawBench is an open **benchmark** for AI web agents — the systems that drive a real browser to complete a user's task end-to-end. It scores agents on real, everyday online tasks (booking flights, ordering groceries, submitting job applications) across live websites.
 
-|[**💻 Github**](https://github.com/reacher-z/ClawBench) | [**🏆 Leaderboard**](https://huggingface.co/spaces/NAIL-Group/clawbench-leaderboard) | [**📖 Paper**](https://arxiv.org/abs/2604.08523) | [**🌐 Website**](https://claw-bench.com) |
+|[**💻 Github**](https://github.com/reacher-z/ClawBench) | [**🏆 Leaderboard**](https://huggingface.co/spaces/TIGER-Lab/ClawBench) | [**📖 Paper**](https://arxiv.org/abs/2604.08523) | [**🌐 Website**](https://claw-bench.com) |
 
-ClawBench is an open **benchmark** for AI web agents — the systems that drive a real browser to complete a user's task end-to-end. It scores agents on real, everyday online tasks (booking flights, ordering groceries, submitting job applications) across live websites. The corpus ships in two slices: **V1 — 153 tasks across 144 websites** (the original frontier-model leaderboard) and **V2 — 130 newer tasks** (expanded coverage). For each run we capture **5 layers of behavioral data** (session replay, screenshots, HTTP traffic, agent reasoning traces, and browser actions), collect human ground-truth, and score with an agentic evaluator that provides step-level traceable diagnostics.
 
-Install: `pip install clawbench-eval` ([PyPI](https://pypi.org/project/clawbench-eval/)) · Companion raw traces: [`NAIL-Group/ClawBenchV1Trace`](https://huggingface.co/datasets/NAIL-Group/ClawBenchV1Trace)
+## 🚀 What's New
+
+- **[2026.05.12]** Added the **V2 corpus** (130 newer tasks across 63 platforms) and 7 new models judged with `deepseek/deepseek-v4-pro` — see snapshot below. Companion V2 traces released at [`TIGER-Lab/ClawBenchV2Trace`](https://huggingface.co/datasets/TIGER-Lab/ClawBenchV2Trace).
+- **[2026.05.04]** Reorganized to the `clawbench-eval` package. Single command for both V1 and V2: `clawbench run --corpus v2 --model <m> --harness hermes`.
+- **[2026.04.18]** Published [`NAIL-Group/ClawBenchV1Trace`](https://huggingface.co/datasets/NAIL-Group/ClawBenchV1Trace) — full 5-layer execution traces (recording, actions, HTTP, agent messages, interception) for every V1 run.
+- **[2026.04.06]** Paper preprint up: [arXiv:2604.08523](https://arxiv.org/abs/2604.08523) — *Can AI Agents Complete Everyday Online Tasks?*
 
 
 ## 🏆 Leaderboard
 
-Live results — pulled from [`leaderboard/results.csv`](https://huggingface.co/datasets/NAIL-Group/ClawBench/blob/main/leaderboard/results.csv) in this repo. Sort by corpus (v1 / v2 / all) and submit your model in the interactive Space:
+Live results — pulled from [`leaderboard/results.csv`](https://huggingface.co/datasets/TIGER-Lab/ClawBench/blob/main/leaderboard/results.csv) in this repo. Filter by corpus (v1 / v2 / all) and submit your model in the interactive Space:
 
-[![Open the live ClawBench Leaderboard ↗](https://img.shields.io/badge/%F0%9F%8F%86%20Open%20the%20live%20Leaderboard-NAIL--Group%2Fclawbench--leaderboard-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000)](https://huggingface.co/spaces/NAIL-Group/clawbench-leaderboard)
+[![Open the live ClawBench Leaderboard ↗](https://img.shields.io/badge/%F0%9F%8F%86%20Open%20the%20live%20Leaderboard-TIGER--Lab%2FClawBench-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000)](https://huggingface.co/spaces/TIGER-Lab/ClawBench)
 
 **V2 snapshot — refreshed 2026-05-12** (full scoring logic: [`eval/scoring.md`](https://github.com/reacher-z/ClawBench/blob/main/eval/scoring.md))
 
@@ -63,11 +67,11 @@ Live results — pulled from [`leaderboard/results.csv`](https://huggingface.co/
 | 6 | `deepseek-v4-flash` | hermes | 3.1% | **1.5%** | 2 / 130 |
 | 7 | `glm-5.1` | openclaw | 0.0% | **0.0%** | 0 / 130 |
 
-**Reward** = fraction that intercepted the final HTTP request AND the LLM judge confirmed the payload fulfilled the instruction. **Intercepted** alone = Stage 1 only. *Partial* = batch attempted fewer than 130 V2 tasks (mid-run abort / queue cap); rates are over attempted, not over 130. Companion traces in [`NAIL-Group/ClawBenchV2Trace`](https://huggingface.co/datasets/NAIL-Group/ClawBenchV2Trace). See [scoring.md](https://github.com/reacher-z/ClawBench/blob/main/eval/scoring.md) for the two-stage rubric, [live leaderboard Space](https://huggingface.co/spaces/NAIL-Group/clawbench-leaderboard) for fresh data + V1.
+**Reward** = fraction that intercepted the final HTTP request AND the LLM judge confirmed the payload fulfilled the instruction. **Intercepted** alone = Stage 1 only. *Partial* = batch attempted fewer than 130 V2 tasks (mid-run abort / queue cap); rates are over attempted, not over 130. Companion traces in [`TIGER-Lab/ClawBenchV2Trace`](https://huggingface.co/datasets/TIGER-Lab/ClawBenchV2Trace). See [scoring.md](https://github.com/reacher-z/ClawBench/blob/main/eval/scoring.md) for the two-stage rubric, [live leaderboard Space](https://huggingface.co/spaces/TIGER-Lab/ClawBench) for fresh data + V1.
 
-**Submit a result** → run [`clawbench-eval`](https://pypi.org/project/clawbench-eval/) on your model and open a PR to [`leaderboard/results.csv`](https://huggingface.co/datasets/NAIL-Group/ClawBench/blob/main/leaderboard/results.csv) — one row per (model × harness × corpus).
+**Submit a result** → run [`clawbench-eval`](https://pypi.org/project/clawbench-eval/) on your model and open a PR to [`leaderboard/results.csv`](https://huggingface.co/datasets/TIGER-Lab/ClawBench/blob/main/leaderboard/results.csv) — one row per (model × harness × corpus).
 
-> **Companion datasets (raw traces):** [`NAIL-Group/ClawBenchV1Trace`](https://huggingface.co/datasets/NAIL-Group/ClawBenchV1Trace) (V1 runs) · [`NAIL-Group/ClawBenchV2Trace`](https://huggingface.co/datasets/NAIL-Group/ClawBenchV2Trace) (V2 runs, rolling) — `recording.mp4`, `requests.jsonl`, `actions.jsonl`, `agent-messages.jsonl`, `interception.json`, `run-meta.json` per model run.
+> **Companion datasets (raw traces):** [`NAIL-Group/ClawBenchV1Trace`](https://huggingface.co/datasets/NAIL-Group/ClawBenchV1Trace) (V1 runs) · [`TIGER-Lab/ClawBenchV2Trace`](https://huggingface.co/datasets/TIGER-Lab/ClawBenchV2Trace) (V2 runs, rolling) — `recording.mp4`, `requests.jsonl`, `actions.jsonl`, `agent-messages.jsonl`, `interception.json`, `run-meta.json` per model run.
 
 ## Dataset Structure
 
@@ -134,7 +138,7 @@ The `eval_schema` field configures the **request interceptor** — a mechanism t
 ```python
 from datasets import load_dataset
 
-ds = load_dataset("NAIL-Group/ClawBench", split="test")
+ds = load_dataset("TIGER-Lab/ClawBench", split="test")
 print(ds[0])
 ```