Papers › TraveLER: A Modular Multi-LMM Agent Framework for Video Question-Answering
TraveLER: A Modular Multi-LMM Agent Framework for Video Question-Answering
Chuyi Shang, Amos You, Sanjay Subramanian, Trevor Darrell, Roei Herzig
Recently, image-based Large Multimodal Models (LMMs) have made significant progress in video question-answering (VideoQA) using a frame-wise approach by leveraging large-scale pretraining in a zero-shot manner. Nevertheless, these models need to be capable of finding relevant information, extracting it, and answering the question simultaneously. Currently, existing methods perform all of these steps in a single pass without being able to adapt if insufficient or incorrect information is collected. To overcome this, we introduce a modular multi-LMM agent framework based on several agents with different roles, instructed by a Planner agent that updates its instructions using shared feedback from the other agents. Specifically, we propose TraveLER, a method that can create a plan to "Traverse" through the video, ask questions about individual frames to "Locate" and store key information, and then "Evaluate" if there is enough information to answer the question. Finally, if there is not enough information, our method is able to "Replan" based on its collected knowledge. Through extensive experiments, we find that the proposed TraveLER approach improves performance on several VideoQA benchmarks without the need to fine-tune on specific datasets. Our code is available at https://github.com/traveler-framework/TraveLER.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Video Question Answering | Perception Test | TraveLER | Accuracy (Top-1) | 50.2 | #5 of 6 | Archive leaderboard | report |
| Video Question Answering | STAR Benchmark | TraveLER (0-shot) | Average Accuracy | 44.9 | #11 of 17 | Archive leaderboard | report |
| Zero-Shot Video Question Answer | EgoSchema (fullset) | TraveLER | Accuracy | 53.3 | #16 of 29 | Archive leaderboard | report |
| Zero-Shot Video Question Answer | NExT-QA | TraveLER (GPT-4) | Accuracy | 68.2 | #13 of 27 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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