Browse State-of-the-Art › Embodied Question Answering
Embodied Question Answering
14 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
14 shown of 14 papers with code (40 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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30 Nov 2017 4 repositories listedWe 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?").
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18 Feb 2025 2 repositories listed Syntology ran 2 of 4 samples · 2 unverified · 4 pointer-only (licence)To bridge this gap, we introduce CityEQA, a new task where an embodied agent answers open-vocabulary questions through active exploration in dynamic city spaces.
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4 Dec 2023 2 repositories listed Syntology ran 10 of 15 samples · 5 unverifiedWe conduct extensive experiments to evaluate the performance and generalizability of our model.
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26 Oct 2018 2 repositories listed Syntology ran 0 of 11 samples · 11 unverified · 11 pointer-only (licence)We use imitation learning to warm-start policies at each level of the hierarchy, dramatically increasing sample efficiency, followed by reinforcement learning.
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14 Jan 2025 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)We introduce Tarsier2, a state-of-the-art large vision-language model (LVLM) designed for generating detailed and accurate video descriptions, while also exhibiting superior general video understanding capabilities.
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2 Dec 2024 1 repository listed Syntology ran 6 of 11 samples · 5 unverified · 11 pointer-only (licence)Experiments show that our method surpasses existing methods on both large scene understanding and existing scene understanding benchmarks.
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6 Jul 2024 1 repository listedTo this end, based on the characteristics of embodied task planning, we first develop a systematic evaluation framework, which encapsulates four crucial capabilities of MFMs: object understanding, spatio-temporal…
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26 May 2024 1 repository listedEmbodied Question Answering (EQA) serves as a benchmark task to evaluate the capability of robots to navigate within novel environments and identify objects in response to human queries.
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1 Feb 2024 1 repository listedTo overcome this limitation, we introduce the Multimodal Embodied Interactive Agent (MEIA), capable of translating high-level tasks expressed in natural language into a sequence of executable actions.
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30 Jul 2023 1 repository listedArtificial intelligence (AI) is expected to be embodied in software agents, robots, and cyber-physical systems that can understand the various contextual information of daily life in the home environment to support…
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28 Aug 2020 1 repository listedThe domain of Embodied AI, in which agents learn to complete tasks through interaction with their environment from egocentric observations, has experienced substantial growth with the advent of deep reinforcement…
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14 Aug 2019 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)The goal of this dataset is to assess question-answering performance from nearly-ideal navigation paths, while considering a much more complete variety of questions than current instantiations of the EQA task.
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9 Apr 2019 1 repository listedTo address this, we propose a modular architecture composed of a program generator, a controller, a navigator, and a VQA module.
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12 Nov 2018 1 repository listed Syntology ran 0 of 2 samples · 2 unverifiedWe explore blindfold (question-only) baselines for Embodied Question Answering.
Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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