| # TempSamp-R1 (no-CoT) baseline on ActivityForensics |
|
|
| TempSamp-R1's official code is not released. The paper's algorithm, however, |
| is a strict subset of what `forensics_grpo` already implements: |
|
|
| | TempSamp-R1 component | Where it lives in forensics_grpo | |
| |-----------------------------------------------|---------------------------------------------------------------------------------| |
| | Mix-policy sampling (G−1 on-policy + 1 GT) | `src/open_r1/trainer/grpo_trainer_video_GT_soft.py` lines ~509, 786-787 | |
| | Non-linear reward shaping (paper Eq. 4) | `transform_rewards` at `grpo_trainer_video_GT_soft.py:692-704` | |
| | Group-relative advantage (paper Eq. 2) | `grpo_trainer_video_GT_soft.py` lines 1102-1106 (default branch) | |
| | IoU reward | `src/open_r1/reward.py::hungarian_iou_reward` (multi-segment) / `forensics_iou` | |
|
|
| So this baseline = `forensics_grpo` trainer + no-CoT prompt + IoU-only reward |
| + all forensics-specific extras disabled. The whole baseline is therefore a |
| ~60-line wrapper plus one launch script — no algorithm is re-implemented. |
|
|
| ## What this enforces |
|
|
| `src/tempsamp_main.py` sets `FORENSICS_COT=false` at import time, then |
| asserts that none of these forensics-specific switches is enabled |
| (they would diverge from the paper algorithm): |
|
|
| - `FORENSICS_DECOMP_ADV` – set-level GT-segment advantage decomposition |
| - `FORENSICS_HUNGARIAN_DECOMP` – per-PRED-segment token-level advantage |
| - `FORENSICS_CTA_GRPO` – counterfactual token-level advantage |
| - `FORENSICS_FORGERY_AWARE` – external forgery-head reward shaping |
| - `FORENSICS_USE_EXTERNAL_VERIFIER`, `FORENSICS_VERIFIER_CONTEXT` |
|
|
| If any of these is true at startup, the script raises. |
|
|
| ## On the "use their IoU" requirement |
|
|
| TempSamp-R1's paper IoU is single-span (Charades-style). ActivityForensics is |
| inherently multi-segment, so this baseline uses the natural multi-segment |
| extension `hungarian_iou_reward`. The reward FORMULA is the same — set-IoU |
| via Hungarian matching reduces to plain IoU when |GT|=|pred|=1. Algorithm |
| (mix-policy + non-linear shaping) is unchanged. |
|
|
| If you want strict single-span IoU instead, switch `--reward_funcs` to `iou` |
| and add a per-segment splitting step to the dataset (mirroring the |
| `data_forensics/` adapter in `../time_r1/`). |
|
|
| ## Files |
|
|
| - `src/tempsamp_main.py` entry point (locks no-CoT, asserts no extras) |
| - `scripts/run_tempsamp_no_cot.sh` launch script |
| - this README |
|
|
| ## Running |
|
|
| ```bash |
| cd /mnt/local-fast/zhangt/baselines/tempsamp_r1 |
| # edit MODEL_PATH / ANNOT_DIR / VIDEO_ROOT / PREPROC_DIR inside the script first |
| bash scripts/run_tempsamp_no_cot.sh |
| ``` |
|
|
| `FORENSICS_GRPO_ROOT` (default `/mnt/local-fast/zhangt/forensics_grpo`) is on |
| `sys.path` so the wrapper imports `src.open_r1.grpo_forensics:main` directly. |
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|
