Pith. sign in

Paper Citation Record · LEDGER

Open Data Synthesis For Deep Research

As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 10 inbound Pith citation observations for arXiv:2509.00375.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.00375 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:45:13.744163Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:12:55.803255Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved29
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 57e90753-9c4b-49c9-abeb-aa7ce9abdfb8 · outbound

This paper cites Next, we conduct the second stage of reinforcement learning.

Open Data Synthesis For Deep Research Next, we conduct the second stage of reinforcement learning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:15.018944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T13:45:13.744163Z digest=sha256:886396d601a2c7cefc65484bb07cc1532988112149d34fac9ec3d6b09edc3a4d

Observation 1c078b26-1e0b-4d38-a34b-834b59fdab0f · outbound

This paper cites Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training.

Open Data Synthesis For Deep Research Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.590993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.590993Z digest=sha256:2d916df9bf81cbbbc0a08b2e2183c353dcbc3da07322d4a66ec375526785d087

Observation c35809ec-5754-4179-91b0-be83303a28b7 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Open Data Synthesis For Deep Research Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.645449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.645449Z digest=sha256:1f2bda6b7943385b36bb6c2c92c6611a45e5ab71bf62e976c1dac710f7c86289

Observation 6c7efccc-5c36-44c2-99e4-801f1d441dc5 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Open Data Synthesis For Deep Research DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.698405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.698405Z digest=sha256:be6d7206e141ffc484d56e03801294cb11daf189bca69905b983db409378c735

Observation ff94a419-327a-4215-91a4-d508473c1573 · outbound

This paper cites Deep Researcher with Test-Time Diffusion.

Open Data Synthesis For Deep Research Deep Researcher with Test-Time Diffusion

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.775915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.775915Z digest=sha256:23bb67550612c0e6aec743ac5a2ae86dacf34b7d557367b439421e375b37987d

Observation df384e68-eb04-4108-971d-c394512442a0 · outbound

This paper cites Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps.

Open Data Synthesis For Deep Research Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.820398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.820398Z digest=sha256:f0f928c721870c903368f387d19ad52d70988f0e79d5c700be8cc592496d6494

Observation 788e5e96-a1c4-4fad-9790-04349983b374 · outbound

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

Open Data Synthesis For Deep Research Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.976736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.976736Z digest=sha256:78fff541c872582fc87f80080be01c912dd66151292d41e8ebeeeb49d27e94be

Observation 4fb63bbe-8308-4a46-9caf-1f2d2c592017 · outbound

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

Open Data Synthesis For Deep Research Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.038009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.038009Z digest=sha256:05e1a3ddcedcc1f83d5131de509937a255f5c9ef53be55a3c6ffa38d7c02a2cc

Observation 82576d0c-c8fa-40f1-8c65-7d048df87609 · outbound

This paper cites 14 Technical report Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al.

Open Data Synthesis For Deep Research 14 Technical report Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:15.457259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T13:45:12.192635Z digest=sha256:fd036eb321cf6b71e59c2b3c9ae0551cf407b7095ee21cfee3118b0cf3e2343d

Observation e0d55f66-e760-45ab-9ef5-242b6d0bcc9b · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

Open Data Synthesis For Deep Research Measuring and Narrowing the Compositionality Gap in Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.298235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.298235Z digest=sha256:8732773d7f21fda05daf8c8e8638673168b87456064a616fdfb75f383e3b55bf

Observation 2e4b11ed-0567-4a90-ae0c-ef4857d241af · outbound

This paper cites Hawkbench: Investigating resilience of rag methods on stratified information-seeking tasks.

Open Data Synthesis For Deep Research Hawkbench: Investigating resilience of rag methods on stratified information-seeking tasks

Reference 18

Resolution
verified exact
raw_fallback, observed 2026-08-05T13:45:14.516694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T13:45:12.418834Z digest=sha256:9f8b32f7749051ed9460fc24c1a259cd8dddec51f256c05a830bc37b4a65ef82

Observation 1941d97a-8332-4671-a5b5-fa55cc4cb781 · outbound

This paper cites Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution.

Open Data Synthesis For Deep Research Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.481722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.481722Z digest=sha256:da9e2c6e4ca53df40a3f009f3d31b4e769fe97c6d268885b448da401b03b9489

Observation 96ae09e3-40bc-4870-8ea4-cd2326ff7d70 · outbound

This paper cites Pangu deepdiver: Adaptive search intensity scaling via open-web reinforcement learning.

Open Data Synthesis For Deep Research Pangu deepdiver: Adaptive search intensity scaling via open-web reinforcement learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.812195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.812195Z digest=sha256:3bb90430c85cc717dd30253553176d4031f4a7a3a29c5f5044720dd2e829cfdd

Observation 23b0208c-f8d2-48f6-aa1c-a6b1e0843da2 · outbound

This paper cites ZeroSearch: Incentivize the Search Capability of LLMs without Searching.

Open Data Synthesis For Deep Research ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.880393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.880393Z digest=sha256:ea8901ad0acbca9b49e794314d80f45f603700d73957a3616bba6f50ed50dbce

Observation 52723a50-cf53-423d-b5c2-90fe0b142f5a · outbound

This paper cites Qwen2 Technical Report.

Open Data Synthesis For Deep Research Qwen2 Technical Report

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.966279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.966279Z digest=sha256:c4c13ac3e112e793fb0948924cd17fda19b404cca358963a2be2d5e4ad31e499

Observation bbfa09ef-40af-4dd6-a06a-e8cf811499b9 · outbound

This paper cites Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

Open Data Synthesis For Deep Research Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.050432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.050432Z digest=sha256:d18139b8b1e7aea153f2dcdd5db28c977814f875b5495016472628c37b1cffd4

Observation 488771f2-8483-4d15-b829-1b80f323ac68 · outbound

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

Open Data Synthesis For Deep Research BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.108221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.108221Z digest=sha256:612dc4b882ec13541ee9264e7bfe7927c182aed8f6d957d76bdef065d911575e

Observation 4acf394a-80e4-4910-87b1-0967ce9e5168 · outbound

This paper cites WebWalker: Benchmarking LLMs in Web Traversal.

Open Data Synthesis For Deep Research WebWalker: Benchmarking LLMs in Web Traversal

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.203875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.203875Z digest=sha256:aca59aecedb27840018a66f7d85f13dcfa4adff4121611773225b281bbc155c8

Observation fa4559d7-d8b0-4e67-9844-968734406a40 · outbound

This paper cites Qwen3 Technical Report.

Open Data Synthesis For Deep Research Qwen3 Technical Report

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.288450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.288450Z digest=sha256:c6ca06dbe8dbecd519e7376c10f24c0848b9c79eb549eb6280f9a044c76201ee

Observation edfbb634-fa44-407f-8a7c-f71cd0a7b2d2 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Open Data Synthesis For Deep Research HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.378399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.378399Z digest=sha256:5b98c0e0ec58cc354a9e864d16ad09f5ebdce37327cb8858248c4013cd7cb9c9

Observation 085b71de-e681-4f06-9644-85c554ffeaa7 · outbound

This paper cites Agentic Information Retrieval.

Open Data Synthesis For Deep Research Agentic Information Retrieval

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.460438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.460438Z digest=sha256:86c1dba0148bc7f3e077f03d75da3550833a036c967cd87f7a78e6abcb14381d

Observation eb491e3e-a787-4dc0-86d4-ec8d280d851b · outbound

This paper cites AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol.

Open Data Synthesis For Deep Research AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.545426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.545426Z digest=sha256:15c8da368486d6a33129ac1c7758178d459d72ba4160aad3e51b10872c196edd

Observation d51a29c2-c421-448f-8281-6e5b4431d019 · outbound

This paper cites Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely.

Open Data Synthesis For Deep Research Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:13.613918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:13.613918Z digest=sha256:343697ca803c84a1da2e9717e40d720334bb83d8793932775232a11c105b0cd1

Observation bc5b8a63-854e-459d-9723-736403b9df16 · outbound

This paper cites shortcut.

Open Data Synthesis For Deep Research shortcut

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:45:15.200744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T13:45:13.674162Z digest=sha256:9c7b3f6ab1b4ba18e5f2194885cae66d81a8db3c5dde74f6b1b188eb7b85e2eb

Observation d1ca22b1-0123-4818-9a96-498baefa963c · outbound

This paper cites RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation.

Open Data Synthesis For Deep Research RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 1976

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.359396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.359396Z digest=sha256:fa0767a774ce099b3aa3609f2142f6c595f7fb1e5f6f298a8cda6035d8f74499

Observation bb9447a8-5dab-4752-bc39-7f055dbbf040 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Open Data Synthesis For Deep Research High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 2009

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.553416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.553416Z digest=sha256:0adac4ffbc75a16a9379d56f47203073d97be5e2255a059d17c998806ccfc670

Observation 51020e55-4f25-442b-abf3-11595a9198b5 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Open Data Synthesis For Deep Research Proximal Policy Optimization Algorithms

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.651316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.651316Z digest=sha256:37c8ad5a6acfa11dbed71dc56ae3eaea78a3413cce1d5f0a4b1dadb539616d47

Observation 990c622e-a4c8-44a6-9332-c6a3a8e7b6a9 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Open Data Synthesis For Deep Research DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.737814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.737814Z digest=sha256:297638710cc4ce211388778da672e47a4555bf49fa854846edd994ff57318a27

Observation b55c6770-84ad-4a04-b6ed-81b4a1a5c535 · outbound

This paper cites WebSailor: Navigating Super-human Reasoning for Web Agent.

Open Data Synthesis For Deep Research WebSailor: Navigating Super-human Reasoning for Web Agent

Reference 2019

Resolution
malformed identifier
no resolver link, observed 2026-08-05T13:45:12.135736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.135736Z digest=sha256:c740b809f4a651545ada361f33d91916a2649208954d1755c245784feca3aa24

Observation 46c89d5a-ce45-45ba-b26a-afcbd3e4536c · outbound

This paper cites OpenAI o1 System Card.

Open Data Synthesis For Deep Research OpenAI o1 System Card

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.868980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.868980Z digest=sha256:da9e4ddac2b8fd064e26426f8e8050a3ac0bc40e3d6b1609d2053ca419ca49e0

Observation 60c71515-6770-4f91-bc24-87c5935698f1 · outbound

This paper cites Scent of knowledge: Optimizing search-enhanced reasoning with information foraging.

Open Data Synthesis For Deep Research Scent of knowledge: Optimizing search-enhanced reasoning with information foraging

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:12.341801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:12.341801Z digest=sha256:247b708e7da2a2938b9795368a10d6442f7885f39afa3fbdbfc1a2abc5e80806

Observation e851582e-a11c-4268-8ab1-04791c355845 · outbound

This paper cites ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning.

Open Data Synthesis For Deep Research ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.469664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.469664Z digest=sha256:c4908e68e460fcd4abe3cd2fe6d200b15cf638b2661ed65fb52b65496e72998a

Observation cbd2aa57-6f18-4acc-b836-73395ee09a68 · outbound

This paper cites RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation.

Open Data Synthesis For Deep Research RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.399188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.399188Z digest=sha256:9c4935300e46d270f6873f1606d368e8c493bf0123946778ad9c65c13b202a93

Observation 010e1081-4ccf-42b1-8b51-87b92f2e4ab1 · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

Open Data Synthesis For Deep Research Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T13:45:11.313077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:45:11.313077Z digest=sha256:bc9ff1b12071ddf03e4f686cdffd6092656e6fb7fcb12375efdcae0471e94c8f

Pith citing papers

Observation 902daa26-e857-4576-90cd-5784b9ca8960 · inbound

Lost in the Maze: Overcoming Context Limitations in Long-Horizon Agentic Search cites this paper.

Lost in the Maze: Overcoming Context Limitations in Long-Horizon Agentic Search Open Data Synthesis For Deep Research

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-04T08:48:44.022931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:48:44.022931Z digest=sha256:ea776a0212ef59826521b0243d60366f552925f087ccff8779e31448cf33a3e1

Observation 2ca88b65-f366-489f-be5c-74f95098c5e1 · inbound

Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning cites this paper.

Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning Open Data Synthesis For Deep Research

Reference 6

Resolution
malformed identifier
arxiv_id, observed 2026-05-16T12:12:51.101340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T12:12:30.041005Z digest=sha256:f02e9904c2a004249c3df855fa2d2652a09229251dc9282475350e02b6a757ea

Observation 1c46dc45-be74-42f4-9ad9-bd745142935a · inbound

Learning to Retrieve from Agent Trajectories cites this paper.

Learning to Retrieve from Agent Trajectories Open Data Synthesis For Deep Research

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-14T01:48:36.098393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T01:47:44.558384Z digest=sha256:3a321c13fd0b50ff0c5557259565875176dd4b01f58d46bb14762258a92e0b66

Observation 8cb3d55a-893c-4926-8b76-e8568037aabb · inbound

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management cites this paper.

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management Open Data Synthesis For Deep Research

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T13:10:26.476983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T13:09:24.304696Z digest=sha256:bb53387a41880f4119e7d5dc179ea63bf35587b132c099ba19c582adbf071f74

Observation 0bb23a1d-8b67-4794-8210-b72fbde161a6 · inbound

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management cites this paper.

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management Open Data Synthesis For Deep Research

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-02T16:18:25.106504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:18:25.106504Z digest=sha256:3f539a643d32fdcc17ab0089e3c5a38f1868ea4404ec638416cdae5c12909581

Observation 5649073c-62e3-48b1-af02-5c3a72e6ec48 · inbound

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents cites this paper.

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents Open Data Synthesis For Deep Research

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:45:52.317362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T01:28:36.266167Z digest=sha256:3f005c4bb6ec520979f12525aca8b5133256b89e91d3e598e600c408caaa4501

Observation 0880bf4e-d718-41d5-a047-668cec95db32 · inbound

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents cites this paper.

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents Open Data Synthesis For Deep Research

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T03:21:19.026653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T03:18:01.006274Z digest=sha256:699ab8d4e38955a7f56bcf7add1d9ee102fbf11c94ac7c7866a2130076f2410b

Observation 988ed784-0343-432a-8af5-6aacf7aa0904 · inbound

FORT-Searcher: Synthesizing Shortcut-Resistant Search Tasks for Training Deep Search Agents cites this paper.

FORT-Searcher: Synthesizing Shortcut-Resistant Search Tasks for Training Deep Search Agents Open Data Synthesis For Deep Research

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T10:27:56.444815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T10:01:45.332920Z digest=sha256:c8b60f11434e88e7cbf4decf7228a1d46be20475a0ea6d57918917f8b9980b48

Observation 5ed714ef-7fed-42ce-b0d1-a26e4501faa2 · inbound

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application cites this paper.

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application Open Data Synthesis For Deep Research

Reference 68

Resolution
metadata mismatch
arxiv_id, observed 2026-06-27T09:50:48.353965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T09:46:30.702256Z digest=sha256:a18e5aeed3b336fbba5f5bd747ec938daa99862b691a82a4ddf780c6917d58c0

Observation cd7621d0-a636-442c-a7f2-f090a868eeb4 · inbound

Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents cites this paper.

Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents Open Data Synthesis For Deep Research

Reference 114

Resolution
unresolved
no resolver link, observed 2026-08-04T15:12:55.803255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T15:12:55.803255Z digest=sha256:9577975350fe9bff4894120b0de97c6459c8a116c19a59c0e2b7c4e8b780016e