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Embodied Question Answering

6 Pith papers cite this work. Polarity classification is still indexing.

6 Pith papers citing it
abstract

We present a new AI task -- Embodied Question Answering (EmbodiedQA) -- where an agent is spawned at a random location in a 3D environment and asked a question ("What color is the car?"). In order to answer, the agent must first intelligently navigate to explore the environment, gather information through first-person (egocentric) vision, and then answer the question ("orange"). This challenging task requires a range of AI skills -- active perception, language understanding, goal-driven navigation, commonsense reasoning, and grounding of language into actions. In this work, we develop the environments, end-to-end-trained reinforcement learning agents, and evaluation protocols for EmbodiedQA.

fields

cs.CV 4 cs.RO 2

years

2026 6

representative citing papers

EAGOR: Embodied Reasoning in Omni-direction

cs.RO · 2026-07-07 · conditional · novelty 7.0

EAGOR reformulates embodied 360-degree directional reasoning as recursive Bayesian estimation on a spherical manifold using spherical harmonics, achieving training-free, rotation-equivariant target tracking.

LIME: Learning Intent-aware Camera Motion from Egocentric Video

cs.RO · 2026-07-02 · unverdicted · novelty 7.0

LIME formulates language-conditioned camera motion as predicting SE(3) target poses from RGB and intent text, using mined multi-intent supervision from egocentric video and a flow-matching pose head.

PInVerify: An Offline Embodied Benchmark for Active Instance Verification

cs.CV · 2026-05-28 · unverdicted · novelty 7.0

PInVerify is a new offline embodied benchmark for active instance verification that supplies multi-view captures and 6-sector navigation topology, with MLLM baselines reaching 85.6% after fine-tuning but showing no reliable benefit from tested next-best-view strategies.

citing papers explorer

Showing 6 of 6 citing papers.

  • EAGOR: Embodied Reasoning in Omni-direction cs.RO · 2026-07-07 · conditional · none · ref 2 · internal anchor

    EAGOR reformulates embodied 360-degree directional reasoning as recursive Bayesian estimation on a spherical manifold using spherical harmonics, achieving training-free, rotation-equivariant target tracking.

  • LIME: Learning Intent-aware Camera Motion from Egocentric Video cs.RO · 2026-07-02 · unverdicted · none · ref 49 · internal anchor

    LIME formulates language-conditioned camera motion as predicting SE(3) target poses from RGB and intent text, using mined multi-intent supervision from egocentric video and a flow-matching pose head.

  • PInVerify: An Offline Embodied Benchmark for Active Instance Verification cs.CV · 2026-05-28 · unverdicted · none · ref 10 · internal anchor

    PInVerify is a new offline embodied benchmark for active instance verification that supplies multi-view captures and 6-sector navigation topology, with MLLM baselines reaching 85.6% after fine-tuning but showing no reliable benefit from tested next-best-view strategies.

  • ReScene: Structured Indoor Scene Reconstruction from Multi-View Captures cs.CV · 2026-06-26 · unverdicted · none · ref 13 · internal anchor

    ReScene introduces HierView for view prioritization and Relation-Aware Assembly for scene graph fusion, reporting 17% lower Chamfer Distance and 26% lower LPIPS than prior baselines on ScanNet while running faster.

  • UpstreamQA: A Modular Framework for Explicit Reasoning on Video Question Answering Tasks cs.CV · 2026-04-25 · unverdicted · none · ref 30

    UpstreamQA disentangles video reasoning by using LRMs for explicit upstream object identification and scene context before downstream LMM VideoQA, improving performance and interpretability on OpenEQA and NExTQA in some cases.

  • LASAR: Towards Spatio-temporal Reasoning with Latent Cognitive Map cs.CV · 2026-05-16 · unverdicted · none · ref 11 · internal anchor

    LASAR pairs a dual-memory system with spatio-temporal contrastive learning to induce latent cognitive maps, reporting 2-3.5% zero-shot gains on VLN-CE and VSI-Bench plus high map self-consistency.