Introduces an interactive episodic memory task with user feedback and a Feedback Alignment Module that improves retrieval accuracy on video benchmarks while remaining efficient.
Groundnlq@ ego4d natural language queries challenge 2023.arXiv preprint arXiv:2306.15255, pages 1–5
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
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cs.CV 3years
2026 3representative citing papers
EgoProx benchmark shows MLLMs have some spatial knowledge but struggle to leverage it for egocentric 3D proximity reasoning VQA.
A hybrid pipeline of OSGNet candidate generation followed by MLLM reranking secured first place in both the Natural Language Queries and GoalStep tracks of the Ego4D Episodic Memory Challenge.
citing papers explorer
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Interactive Episodic Memory with User Feedback
Introduces an interactive episodic memory task with user feedback and a Feedback Alignment Module that improves retrieval accuracy on video benchmarks while remaining efficient.
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EgoProx: Evaluating MLLMs on Egocentric 3D Proximity Reasoning Across a Cognitive Hierarchy
EgoProx benchmark shows MLLMs have some spatial knowledge but struggle to leverage it for egocentric 3D proximity reasoning VQA.
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OSGNet with MLLM Reranking @ Ego4D Episodic Memory Challenge 2026
A hybrid pipeline of OSGNet candidate generation followed by MLLM reranking secured first place in both the Natural Language Queries and GoalStep tracks of the Ego4D Episodic Memory Challenge.