We lifted 23 functions out of this paper's own repositories and ran 17 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| sczwangxiao/video-flexreduc | canonical | 17 of 23 |
| Function | Status | Where it lives |
|---|---|---|
| repeat_kv | Ran | sczwangxiao/video-flexreduc/retake/longvideo_cache.py code served (permissive licence) · get_code("3c76e52815c5401d") |
| evaluate_mlvu_generation | Ran | sczwangxiao/video-flexreduc/retake/dataset_utils.py code served (permissive licence) · get_code("81664204c8525de9") |
| gather_results | Ran | sczwangxiao/video-flexreduc/retake/infer_eval.py code served (permissive licence) · get_code("e1e87b90e35fb630") |
| load_yaml | Ran | sczwangxiao/video-flexreduc/retake/infer_eval.py code served (permissive licence) · get_code("d37f4e5bd2ad847b") |
| memory_bank_compress_MALLM | Ran | sczwangxiao/video-flexreduc/retake/visual_compression.py code served (permissive licence) · get_code("6ad69145ddabafe5") |
| memory_bank_compress_MALLM_hard | Ran | sczwangxiao/video-flexreduc/retake/visual_compression.py code served (permissive licence) · get_code("5f9f5bd51036cfc1") |
| memory_bank_compress_keyframe | Ran | sczwangxiao/video-flexreduc/retake/visual_compression.py code served (permissive licence) · get_code("0366d231d1eb184f") |
| patch_llava_onevision_config | Ran | sczwangxiao/video-flexreduc/retake/monkeypatch.py code served (permissive licence) · get_code("a83c7315b78d5c2c") |
| patch_qwen2_5_vl_config | Ran | sczwangxiao/video-flexreduc/retake/monkeypatch.py code served (permissive licence) · get_code("d7609a472ef2dd0d") |
| patch_qwen2vl_config | Ran | sczwangxiao/video-flexreduc/retake/monkeypatch.py code served (permissive licence) · get_code("8601a846757deb14") |
| retake_LlavaOnevisionForConditionalGeneration_get_chunk_size | Ran | sczwangxiao/video-flexreduc/retake/llava_onevision.py code served (permissive licence) · get_code("8a68c201ee613f88") |
| retake_LlavaOnevisionForConditionalGeneration_segment_input_ids | Ran | sczwangxiao/video-flexreduc/retake/llava_onevision.py code served (permissive licence) · get_code("7ddc25ea1dac67d2") |
| retake_Qwen2VLForConditionalGeneration_segment_input_ids | Ran | sczwangxiao/video-flexreduc/retake/qwen2_vl.py code served (permissive licence) · get_code("eab30ba8c4d44a11") |
| retake_Qwen2_5_VLForConditionalGeneration_get_chunk_size | Ran | sczwangxiao/video-flexreduc/retake/qwen2_5_vl.py code served (permissive licence) · get_code("e5124ec09df7329d") |
| retake_Qwen2_5_VLForConditionalGeneration_segment_input_ids | Ran | sczwangxiao/video-flexreduc/retake/qwen2_5_vl.py code served (permissive licence) · get_code("676b41a7d2ba0916") |
| rotate_half | Ran | sczwangxiao/video-flexreduc/retake/longvideo_cache.py code served (permissive licence) · get_code("e03d53ba9d4f9ae5") |
| trimm_results | Ran | sczwangxiao/video-flexreduc/retake/infer_eval.py code served (permissive licence) · get_code("2a31a1d556220646") |
| apply_multimodal_rotary_pos_emb | Not yet run | sczwangxiao/video-flexreduc/retake/longvideo_cache.py code served (permissive licence) · get_code("8971bec8b941516b") |
| eval_mlvu_results | Not yet run | sczwangxiao/video-flexreduc/retake/dataset_utils.py code served (permissive licence) · get_code("1c4242b450f2a4ac") |
| eval_videomme_results | Not yet run | sczwangxiao/video-flexreduc/retake/dataset_utils.py code served (permissive licence) · get_code("feee0c01f58c3b2e") |
| retake_Qwen2VLAttention_forward | Not yet run | sczwangxiao/video-flexreduc/retake/qwen2_vl.py code served (permissive licence) · get_code("b9e6d7a085769799") |
| retake_Qwen2VLForConditionalGeneration_compress_video_tokens | Not yet run | sczwangxiao/video-flexreduc/retake/qwen2_vl.py code served (permissive licence) · get_code("508f605be1850961") |
| retake_Qwen2_5_VLAttention_forward | Not yet run | sczwangxiao/video-flexreduc/retake/qwen2_5_vl.py code served (permissive licence) · get_code("8104fe56ba8a1b10") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Multimodal Large Language Models (MLLMs) have revolutionized video understanding, yet are still limited by context length when processing long videos. Recent methods compress videos by leveraging visual redundancy uniformly, yielding promising results. Nevertheless, our quantitative analysis shows that redundancy varies significantly across time and model layers, necessitating a more flexible compression strategy. We propose AdaReTaKe, a training-free method that flexibly reduces visual redundancy by allocating compression ratios among time and layers with theoretical guarantees. Integrated into state-of-the-art MLLMs, AdaReTaKe improves processing capacity from 256 to 2048 frames while preserving critical information. Experiments on VideoMME, MLVU, LongVideoBench, and LVBench datasets demonstrate that AdaReTaKe outperforms existing methods by 2.3% and 2.8% for 7B and 72B models, respectively, with even greater improvements of 5.9% and 6.0% on the longest LVBench. Our code is available at https://github.com/SCZwangxiao/video-FlexReduc.git.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2503.12559")
get_code_for_paper("2503.12559")
have("2503.12559")
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