DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments | Paper Citation Record

Observation a302ecf0-7aab-4957-86e5-b71a8b4ceaa6 · outbound

This paper cites Self-RAG : Learning to retrieve, generate, and critique through self-reflection.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Self-RAG : Learning to retrieve, generate, and critique through self-reflection

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.362916Z

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Observation 3fd44d94-8aa0-4cce-b1b0-7abd5885881f · outbound

This paper cites Benchmarking large language models in retrieval-augmented generation.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Benchmarking large language models in retrieval-augmented generation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.407939Z

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Observation 087a70de-e1d6-43c4-8c3e-a932de9f66b9 · outbound

This paper cites BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.495212Z

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Observation 1a102dd7-26a8-4f18-87f4-d76c736dd404 · outbound

This paper cites The power of noise: Redefining retrieval for RAG systems.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments The power of noise: Redefining retrieval for RAG systems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.576961Z

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Observation d3fce4c0-e569-48d4-b4d2-3d5836a235ea · outbound

This paper cites InteractComp: Evaluating Search Agents With Ambiguous Queries.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments InteractComp: Evaluating Search Agents With Ambiguous Queries

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.639364Z

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Observation 8a21d8bf-4f7c-4c0b-a1ac-e2b9325ba385 · outbound

This paper cites Mind2Web : Towards a generalist agent for the web.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Mind2Web : Towards a generalist agent for the web

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.696841Z

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Observation 31a707f2-89e4-442c-8cce-3d0aa584e0d6 · outbound

This paper cites Enabling large language models to generate text with citations.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Enabling large language models to generate text with citations

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.790279Z

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Observation 47de9def-c6ef-4b8c-bbe6-307e3b9653cd · outbound

This paper cites Large language models cannot self-correct reasoning yet.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Large language models cannot self-correct reasoning yet

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.871204Z

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Observation e4819322-b758-436c-be22-9509f0de1a39 · outbound

This paper cites Survey of hallucination in natural language generation.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Survey of hallucination in natural language generation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:48.946310Z

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Observation fc3eae84-44d1-416b-b83f-9c6812745797 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.047071Z

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Observation 4ebc4be2-8a1e-4196-a517-ad28fa53ec7e · outbound

This paper cites Dense passage retrieval for open-domain question answering.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Dense passage retrieval for open-domain question answering

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.098388Z

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Observation ccc8f459-a55a-4a6f-a86a-6967a6d413d2 · outbound

This paper cites u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \

Reference 12

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Observation 5027daa3-2cb5-47ee-a96f-15307575cdc8 · outbound

This paper cites Entity-based knowledge conflicts in question answering.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Entity-based knowledge conflicts in question answering

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.195723Z

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Observation e00d7f77-85f8-49b9-945a-30f86d347030 · outbound

This paper cites Self-Refine : Iterative refinement with self-feedback.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Self-Refine : Iterative refinement with self-feedback

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.276903Z

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Observation a784d6c6-357c-4f6c-8b73-e41b9b9789b6 · outbound

This paper cites GAIA : a benchmark for general AI assistants.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments GAIA : a benchmark for general AI assistants

Reference 15

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Observation 27e21187-0083-4d61-904c-192dac824c12 · outbound

This paper cites FActScore : Fine-grained atomic evaluation of factual precision in long form text generation.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments FActScore : Fine-grained atomic evaluation of factual precision in long form text generation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.441867Z

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Observation b3026955-af08-4d11-bd8e-c87f2e9fd5bd · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments WebGPT: Browser-assisted question-answering with human feedback

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.526685Z

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Observation 5c6604d0-5cbb-4039-b99e-476e3d3a52ab · outbound

This paper cites On the risk of misinformation pollution with large language models.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments On the risk of misinformation pollution with large language models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.617131Z

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Observation 9f9430e7-baa4-4a53-bc03-722d8c1dd1ad · outbound

This paper cites Tell me more! towards implicit user intention understanding of language model driven agents.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Tell me more! towards implicit user intention understanding of language model driven agents

Reference 19

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Observation cc042a88-9acf-4e27-8c21-6e5899611d24 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Toolformer: Language models can teach themselves to use tools

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:49.757617Z

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Observation 7e865149-129d-42d3-8c6f-7ef6bc5e22c3 · outbound

This paper cites Towards understanding sycophancy in language models.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Towards understanding sycophancy in language models

Reference 21

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Observation 46d162ac-b9c6-4384-8ed9-d93c46e01de2 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Reflexion: Language agents with verbal reinforcement learning

Reference 22

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Observation 8abf6510-6d49-450f-920f-5033fb5b907c · outbound

This paper cites FEVER : a large-scale dataset for fact extraction and VER ification.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments FEVER : a large-scale dataset for fact extraction and VER ification

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:50.162196Z

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Observation fcc34e7a-1047-4684-a31a-a9b8d2d34290 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Chain-of-thought prompting elicits reasoning in large language models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:50.315268Z

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Observation af24c92a-46cd-4183-a95a-4a974bf07c1f · outbound

This paper cites BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:50.419774Z

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Observation a1ae14c5-955d-4c88-8cac-20e311514e66 · outbound

This paper cites WebWalker : Benchmarking LLMs in web traversal.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments WebWalker : Benchmarking LLMs in web traversal

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:50.539216Z

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Observation 118c5f78-2fb3-470c-912b-082c0aaaca96 · outbound

This paper cites Knowledge conflicts for LLMs : A survey.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Knowledge conflicts for LLMs : A survey

Reference 27

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Observation e9b249ed-0017-4c05-82c0-216a1b371d4b · outbound

This paper cites Narasimhan, and Yuan Cao.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Narasimhan, and Yuan Cao

Reference 28

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Observation 5fbf085d-a3d0-4284-a062-5189c386e136 · outbound

This paper cites $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:50.883343Z

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Observation 14afcf14-edf6-4119-92ce-93c9e0096223 · outbound

This paper cites WebArena : A realistic web environment for building autonomous agents.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments WebArena : A realistic web environment for building autonomous agents

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:51.036837Z

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Observation 2626c290-ef7a-4cad-af9b-d8d16cad648d · outbound

This paper cites PoisonedRAG : Knowledge corruption attacks to Retrieval-Augmented generation of large language models.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments PoisonedRAG : Knowledge corruption attacks to Retrieval-Augmented generation of large language models

Reference 31

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Observation d8f26253-572f-4248-9ecc-71e2ff060956 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 32

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Observation 24386697-1ff7-4160-97f4-4663c22a6651 · outbound

This paper cites International Conference on Learning Representations,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments International Conference on Learning Representations,

Reference 33

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 34

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Observation 68c8cb30-307d-403e-be00-026087f6a092 · outbound

This paper cites an unresolved cited work.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 35

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Observation ca9f41df-acd7-492f-97c2-308b90aa48de · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Retrieval-augmented generation for knowledge-intensive

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:51.905269Z

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Observation 3a7d9e27-96f2-46f5-8352-3a5782ff7789 · outbound

This paper cites Proceedings of the 2020 conference on empirical methods in natural language processing,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Proceedings of the 2020 conference on empirical methods in natural language processing,

Reference 37

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Observation f6386fb2-2cc8-46f7-a8a3-7db6374717fb · outbound

This paper cites Advances in neural information processing systems,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Advances in neural information processing systems,

Reference 38

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Observation cc2ca09c-7579-4a99-8af9-9b2fb4a0fa83 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 39

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Observation 9a2fe180-8d98-4edc-ae97-5f024eb42f54 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , year=.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , year=

Reference 40

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 41

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Observation a9550cff-415e-4372-9de5-a084da42943d · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 42

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This paper cites Narasimhan and Yuan Cao , title =.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Narasimhan and Yuan Cao , title =

Reference 43

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 44

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Observation 98bb099f-f976-4953-b67d-8cf757c8787b · outbound

This paper cites an unresolved cited work.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 45

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Observation b88c4ed1-6cc5-4d60-b120-4767088bf492 · outbound

This paper cites an unresolved cited work.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 46

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Observation cb3e5076-8324-4f9a-b3df-077ce9150a9e · outbound

This paper cites International Conference on Learning Representations,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments International Conference on Learning Representations,

Reference 47

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Observation 7a4291d9-4e4e-4afc-bd18-a5dab6a63273 · outbound

This paper cites Proceedings of the 2021 conference on empirical methods in natural language processing , year=.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Proceedings of the 2021 conference on empirical methods in natural language processing , year=

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:52.932355Z

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Observation ac8c6a14-45ca-4811-9709-0b2ae0c71c48 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Knowledge conflicts for

Reference 49

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Observation 3404e851-8364-4f91-b112-042520531c5b · outbound

This paper cites Findings of the association for computational linguistics: EMNLP 2023 , year=.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Findings of the association for computational linguistics: EMNLP 2023 , year=

Reference 50

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Observation 75d32e88-8c6e-44d6-9d46-3326682625df · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 51

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Observation a0864b6d-45bd-4ac5-93bd-0ea9cc4af7c3 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Proceedings of the AAAI Conference on Artificial Intelligence , year=

Reference 52

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Observation 7177693f-58f2-4ffc-8829-d85a4fb47a2b · outbound

This paper cites The power of noise: Redefining retrieval for.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments The power of noise: Redefining retrieval for

Reference 53

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Observation cd5f14d6-be07-42d5-976e-efd91c1c88ea · outbound

This paper cites an unresolved cited work.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 54

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Observation dbd07658-8d80-488e-96a2-de381090796f · outbound

This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , year=.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , year=

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:53.755816Z

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Observation 6f227416-7b62-4e30-a457-5d7bb19384c1 · outbound

This paper cites International conference on learning representations,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments International conference on learning representations,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:53.888810Z

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Observation 7c687296-3b47-4cfb-b3f3-0b165ab31ad9 · outbound

This paper cites Advances in neural information processing systems,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Advances in neural information processing systems,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:54.071638Z

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Observation 0623ac8f-3949-412d-a6c7-c9aa8aa58b40 · outbound

This paper cites Advances in neural information processing systems,.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Advances in neural information processing systems,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-01T18:30:54.191828Z

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Observation 8095dc41-b30b-49b3-933c-4cafb2caa247 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments ACM computing surveys , volume=

Reference 59

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Observation 2c080c04-1acf-480a-a183-5fe5f80c52a2 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 60

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Observation b8e53f1d-9d21-43ff-b06f-ac972076c0f0 · outbound

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DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

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Observation 3aa868db-6bbe-43e0-ad86-48085ab17bd7 · outbound

This paper cites an unresolved cited work.

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments Unresolved cited work

Reference 62

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Pith citing papers