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BIGC team wins NLPCC 2026 task with novel video grounding system

By PulseAugur Editorial · [1 sources] ·

Researchers from the Beijing Institute of Graphic Communication (BIGC) have developed a novel system called DAEP for the NLPCC 2026 Shared Task 1 Track 3. This system excels at temporal answer grounding in medical video corpora, a task that involves identifying the correct video from a set of 50 candidates and pinpointing the specific segment that answers a given question. DAEP achieved first place in the official evaluation, outperforming ten other systems with an average score of 0.2728. AI

IMPACT This system's success in temporal answer grounding for medical videos could advance AI's capabilities in medical diagnostics and information retrieval from multimedia content.

RANK_REASON The cluster describes a research paper detailing a system that won a shared task competition. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

BIGC team wins NLPCC 2026 task with novel video grounding system

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The cluster describes a research paper detailing a system that won a shared task competition. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Tianjian He, Yujie Liu, Zhiping Huang, Changbo Xu ·

    DAEP: Difficulty-Aware Evidence Planning for Medical Video Corpus Temporal Answer Grounding

    arXiv:2608.06869v1 Announce Type: cross Abstract: We describe DAEP, team BIGC's submission to NLPCC 2026 Shared Task 1 Track 3: Difficulty-Aware Temporal Answer Grounding in Video Corpus (DA-TAGVC). The task requires retrieving the target video from 50 candidates and localizing t…

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