| # Experiment Summary |
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| This file summarizes the experiments run in `SGL_new` during the current iteration. |
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| ## 1. Main Model Variants |
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| - `2B vision + 1B text/mlp1` hybrid |
| - `shared_vision`: `2B guide + 8B decode` |
| - optional guidance variants on top of `shared_vision`: |
| - `guide_text_mode=short_rationale` |
| - `guide_reasoning_mode=short_cot` |
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| ## 2. 2B Vision + 1B Text Hybrid |
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| Checkpoint build: |
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| - hybrid checkpoint: `/home/yf/snap/data/yf/InternVL2-1B_2Bvision_hybrid` |
| - build script: [build_hybrid_checkpoint_2bvision_1bllm.sh](/home/yf/snap/SGL_new/build_hybrid_checkpoint_2bvision_1bllm.sh:1) |
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| TextVQA 50-sample results: |
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| | Mode | Accuracy | Result file | |
| | --- | ---: | --- | |
| | normal inference | `0.652000` | `/home/yf/snap/SGL_new/outputs/textvqa_largeonly_hybrid_2bvision_1bllm_validation50/textvqa_val_hybrid_2bvision_1bllm_limit50.json` | |
| | `reasoning-mode=two_pass` | `0.488000` | `/home/yf/snap/SGL_new/outputs/textvqa_largeonly_hybrid_2bvision_1bllm_cot50/textvqa_val_hybrid_2bvision_1bllm_two_pass_limit50.json` | |
| | `reasoning-mode=prompt` | `0.000000` | `/home/yf/snap/SGL_new/outputs/textvqa_largeonly_hybrid_2bvision_1bllm_prompt50/textvqa_val_hybrid_2bvision_1bllm_prompt_limit50.json` | |
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| Takeaway: |
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| - For the `1B hybrid`, direct CoT prompting hurts TextVQA answer formatting. |
| - `prompt` mode is the worst because it pushes the model to emit explanatory sentences instead of short answers. |
| - `two_pass` is better than `prompt`, but still clearly worse than normal inference. |
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| ## 3. Shared Vision 50-Sample Ablations |
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| Common setup: |
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| - guide checkpoint: `/home/yf/snap/data/yf/InternVL2-2B` |
| - decode checkpoint: `/home/yf/snap/data/yf/InternVL2-8B` |
| - `large-model-prune-layer=0.0` |
| - `large-model-prune-ratio=0.4` |
| - `consistency-token-ratio=0.05` |
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| Results: |
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| | Variant | Accuracy | Result file | |
| | --- | ---: | --- | |
| | baseline | `0.734000` | `/home/yf/snap/SGL_new/outputs/shared_vision_baseline50/textvqa_shared_vision_baseline_limit50.json` | |
| | `guide_text_mode=short_rationale` | `0.628000` | `/home/yf/snap/SGL_new/outputs/shared_vision_guide_text50/textvqa_shared_vision_guide_text_limit50.json` | |
| | `guide_reasoning_mode=short_cot` | `0.734000` | `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention50/textvqa_shared_vision_guide_attention_limit50.json` | |
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| Takeaway: |
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| - Short text hints hurt on this 50-sample slice. |
| - Short CoT in the guide branch does not improve accuracy on this slice, but it does not hurt either. |
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| ## 4. Did Guide CoT Change Attention? |
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| Answer: yes. |
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| Distribution comparison between: |
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| - baseline: `/home/yf/snap/SGL_new/outputs/shared_vision_baseline50_stats/textvqa_shared_vision_baseline_limit50_stats.json` |
| - `short_cot`: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention50_stats/textvqa_shared_vision_guide_attention_limit50_stats.json` |
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| Measured differences over the same 50 samples: |
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| - `avg_l1 = 0.133287` |
| - `median_l1 = 0.123993` |
| - `avg_jsd = 0.004375` |
| - `avg_top16_overlap = 13.48 / 16` |
| - `top1_same_count = 50 / 50` |
| - `avg_entropy_delta = +0.113141` |
| - `changed_small_answer_count = 38 / 50` |
| - `changed_large_answer_count = 2 / 50` |
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| Interpretation: |
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| - Guide CoT changes the visual-token importance distribution. |
| - The main effect is on the secondary mass / overall spread, not on the single top token. |
| - On this slice, attention changes did not convert into a net accuracy gain. |
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| ## 5. Explicit CoT Prompting in Guide Branch |
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| An `explicit_cot` guide mode was prototyped to force a more explicit reasoning format. |
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| Smoke result: |
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| - output: `/home/yf/snap/SGL_new/outputs/vqav2_on_correct_off_wrong_shared_vision_explicitcot_smoke10/vqav2_on_correct_off_wrong_shared_vision_explicitcot_smoke10.json` |
| - observed behavior: the model only partially followed the intended `Reasoning / Answer` structure |
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| Takeaway: |
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| - Harder prompting is still not enough to guarantee stable step-by-step reasoning format. |
| - The current guide CoT remains prompt-level control, not a true multi-pass reasoning mechanism. |
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| ## 6. `on_correct_off_wrong_nontrunc.json` Cases |
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| Important finding: |
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| - `/home/yf/snap/SGL_new/data/textvqa/on_correct_off_wrong_nontrunc.json` is not aligned with the current `TextVQA val` cache. |
| - These cases match `/home/yf/snap/data/yf/sgl_vqav2_cache/vqav2_val.jsonl`. |
| - In practice, this file is a VQAv2-style case list, despite living under `textvqa/`. |
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| Helper used: |
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| - [run_shared_vision_cases.py](/home/yf/snap/SGL_new/tools/run_shared_vision_cases.py:1) |
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| 74-case results on this set: |
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| | Variant | Accuracy | Result file | |
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| | baseline | `0.896396` | `/home/yf/snap/SGL_new/outputs/vqav2_on_correct_off_wrong_shared_vision_baseline/vqav2_on_correct_off_wrong_shared_vision_baseline.json` | |
| | `guide_reasoning_mode=short_cot` | `0.896396` | `/home/yf/snap/SGL_new/outputs/vqav2_on_correct_off_wrong_shared_vision_shortcot/vqav2_on_correct_off_wrong_shared_vision_shortcot.json` | |
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| Takeaway: |
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| - On these 74 VQAv2-style cases, enabling short CoT in the guide branch did not change overall accuracy. |
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| ## 7. Full TextVQA Runs |
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| Two full `shared_vision + short_cot guide-attention` runs were launched and completed. |
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| ### Keep40 |
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| - output dir: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention_full_20260429_115658` |
| - result file: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention_full_20260429_115658/textvqa_shared_vision_guide_attention_full.json` |
| - summary file: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention_full_20260429_115658/textvqa_shared_vision_guide_attention_full.summary.json` |
| - final accuracy: `0.764260` |
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| ### Keep09 |
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| - output dir: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention_keep09_full_20260429_130806` |
| - result file: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention_keep09_full_20260429_130806/textvqa_shared_vision_guide_attention_keep09_full.json` |
| - summary file: `/home/yf/snap/SGL_new/outputs/shared_vision_guide_attention_keep09_full_20260429_130806/textvqa_shared_vision_guide_attention_keep09_full.summary.json` |
| - final accuracy: `0.744660` |
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| ## 8. Code Changes Relevant to These Experiments |
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| - shared-vision core: [run_shared_vision_guided_textvqa.py](/home/yf/snap/SGL_new/eval/vqa/run_shared_vision_guided_textvqa.py:1) |
| - shared-vision launcher: [textvqaSharedVision-2Bguide-8Btext.sh](/home/yf/snap/SGL_new/textvqaSharedVision-2Bguide-8Btext.sh:1) |
| - keep40/keep09 launcher: [run_textvqa_shared_vision_keep40_keep09.sh](/home/yf/snap/SGL_new/run_textvqa_shared_vision_keep40_keep09.sh:1) |
| - case runner: [run_shared_vision_cases.py](/home/yf/snap/SGL_new/tools/run_shared_vision_cases.py:1) |
| - hybrid single-model eval: [run_single_model_native.py](/home/yf/snap/SGL_new/eval/vqa/run_single_model_native.py:1) |
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| ## 9. Practical Conclusions |
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| - For the `1B hybrid`, normal inference is the safest option so far. |
| - For `shared_vision`, short text hints are currently harmful on the tested slice. |
| - Short CoT in the guide branch changes attention distributions, but does not yet give consistent accuracy gains. |
| - If the goal is real step-by-step guide reasoning, prompt-only control is not enough; a true multi-pass guide mechanism is the next logical step. |
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