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Paper Citation Record · LEDGER

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2505.22942.

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

pith.paper-citation-record.v1
2505.22942 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:01:25.268734Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-16T09:33:30.444057Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T09:37:41.944603Z

Reference resolution

53 of 53 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved51
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6d3f758-f93f-4b9f-b296-2cfa105bc81d · outbound

This paper cites online" 'onlinestring :=.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning online" 'onlinestring :=

Reference 1

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no resolver link, observed 2026-08-07T13:01:20.246771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:20.246771Z digest=sha256:015a46c614ab3bc47b405e5223ade6de2b3cd44ce59f601a4f6d5deeba9f0f13

Observation 555dd279-badd-41eb-8dc7-0608c3a6e1a1 · outbound

This paper cites write newline.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning write newline

Reference 2

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no resolver link, observed 2026-08-07T13:01:20.386292Z

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source=arxiv_source observed=2026-08-07T13:01:20.386292Z digest=sha256:f56c7fb9c3fa8857e42d971483823f0c81b7a41ff3f946aff93142aac07c347b

Observation 5c05b1af-4175-41d1-8cdf-042686b4f6e9 · outbound

This paper cites Nemotron-4 340B Technical Report.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Nemotron-4 340B Technical Report

Reference 3

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no resolver link, observed 2026-08-07T13:01:20.532944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:20.532944Z digest=sha256:47e5b72b81e45808e77afd2097f09e7993fa734c9b18cad832d003610483b1a7

Observation 24c6ddbe-1b80-431a-a7c6-a1457d379561 · outbound

This paper cites SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents

Reference 4

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no resolver link, observed 2026-08-07T13:01:20.699288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:20.699288Z digest=sha256:a783ffcaf83f5792efa88dd3b8d10c21fe3e3b1e800b914a1a31bcde30fbdff7

Observation 073aff89-ce94-4cf9-a649-f8929e728b63 · outbound

This paper cites The BrowserGym Ecosystem for Web Agent Research.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning The BrowserGym Ecosystem for Web Agent Research

Reference 5

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no resolver link, observed 2026-08-07T13:01:20.809475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:20.809475Z digest=sha256:a9868be4ca04e070b1f11cd0a7b9898686dabdbf07425c47a2a3dc9b0f262a53

Observation 9d04ee0b-94c0-4b75-9ba7-8a62058bd972 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:28.232626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:20.888771Z digest=sha256:604f5cf291c094c909a1327f4408a3c002bc4577c91dcbd1955b2a5b305c0bb9

Observation 4f3f1d3d-9b9b-4994-9aa0-26ef3b260ce3 · outbound

This paper cites Laradji, Manuel Del Verme, Tom Marty, David Vazquez, Nicolas Chapados, and Alexandre Lacoste.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Laradji, Manuel Del Verme, Tom Marty, David Vazquez, Nicolas Chapados, and Alexandre Lacoste

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:28.060460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:20.987141Z digest=sha256:14007109a0438412c642a480b70c48a7831386d531277898007d6dcea400a5f2

Observation 0339ea42-1057-4d10-864d-f1d8e9ec2727 · outbound

This paper cites The Llama 3 Herd of Models.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning The Llama 3 Herd of Models

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.057274Z digest=sha256:47ce374d5bfd46060f2f9975d6eb11d3103ac333ebec084ec2c410401312e21d

Observation 5d477bd3-3331-4e95-9d3d-2fbb01500ea4 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 9

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raw_fallback, observed 2026-08-07T13:01:27.887314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:21.126022Z digest=sha256:31410988084da5de40ff6bf50eeee80f5c3c08e7a116920874d08ffa05515d99

Observation 24b2fc55-e79a-4c59-9716-f6d51fe25a70 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 10

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no resolver link, observed 2026-08-07T13:01:21.198579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.198579Z digest=sha256:82fb3b26020c11a394b7ccbbfef3fa30c2c9c9574932e42251226734b564f9bb

Observation 83b894f4-da58-41bd-b9fd-b69d32ac0f09 · outbound

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

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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no resolver link, observed 2026-08-07T13:01:21.278424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.278424Z digest=sha256:6ba08e4dc30b657b12cac1ba7d6d3c02af4272d802350839adead2cdff98736c

Observation 68a133eb-d901-42e3-9210-9afdc67ce733 · outbound

This paper cites A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis

Reference 12

Resolution
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no resolver link, observed 2026-08-07T13:01:21.382104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.382104Z digest=sha256:157eb5a14cec13ac117eb11d7147070aa4e628ae8a9b1c1c9dc8e2bb720ed4bd

Observation b17aeedb-adc1-4c61-b128-beb80f898367 · outbound

This paper cites WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:21.513024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.513024Z digest=sha256:efa4adb7025667a46c9d105488ab1ae3d1234724e04e23b52c53a294c18823d6

Observation 60e58c5d-6d0d-4c86-bada-cbe80b64a804 · outbound

This paper cites OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization

Reference 14

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unresolved
no resolver link, observed 2026-08-07T13:01:21.608317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.608317Z digest=sha256:336851782f4bf6a20b99c7470d157aa5ecadf59e97f6c75a8c418df48194c48e

Observation 337f8532-e1f3-4e5b-86e5-2c897efd69c0 · outbound

This paper cites GPT-4o System Card.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning GPT-4o System Card

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:21.704241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.704241Z digest=sha256:c32ef3bb3af766e155fd2b88fcdd441626b1d40e62d2e516b9000531eff2fc15

Observation 233fcc62-c834-4818-b132-b3642fa84a08 · outbound

This paper cites VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:21.774280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:21.774280Z digest=sha256:e52a2469dc65075ac45b911a3e5d0345b9ef87cc3dcf4647c72f6f02947ab18b

Observation 18091e6e-8d27-4e9c-8127-a67f3eceb49c · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 17

Resolution
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raw_fallback, observed 2026-08-07T13:01:27.722297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:21.867543Z digest=sha256:b6a8aa80331a556b281bb5d4b4bacc1d9dd56d7edbc0f0a4710f50c09a7698cb

Observation bddcc80b-d7c3-4d49-969a-4b5a4bd78c04 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 18

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raw_fallback, observed 2026-08-07T13:01:27.545256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:21.945890Z digest=sha256:caf2b284d4b48949e0f715b6ce73713498aadc15ab4d794892be8da871698585

Observation ee25ebe5-b132-47da-b113-31e06bc30f82 · outbound

This paper cites ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.017252Z digest=sha256:7ce7e39429abf3f00f76c613964f7cf905f484fe746d379eec7255932e577cfc

Observation 6658e12c-bddd-42d5-8bbc-633daa5d0b52 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 20

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no resolver link, observed 2026-08-07T13:01:22.120072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.120072Z digest=sha256:5e1abe7cd3187a6500c12ea8aa4d37638f05f7b201a9e34e24b9c7166829912f

Observation 7c90a064-4a20-49b5-83b6-be24acdb7b0b · outbound

This paper cites ReflecTool: Towards Reflection-Aware Tool-Augmented Clinical Agents.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning ReflecTool: Towards Reflection-Aware Tool-Augmented Clinical Agents

Reference 21

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no resolver link, observed 2026-08-07T13:01:22.236158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.236158Z digest=sha256:7b238a44de312265e60837ff86ba4709bc3790818cfb47bb5f2977899057632c

Observation c5e43736-43ad-4bde-a342-009c3178061d · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning AgentBench: Evaluating LLMs as Agents

Reference 22

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no resolver link, observed 2026-08-07T13:01:22.351667Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.351667Z digest=sha256:a32887b88cb5434c982d2b77e59df523d52cbd1d79b214f28ed77ed2f3aafbce

Observation 0fa1ecbc-8652-4784-99a3-ed2dbcd2078e · outbound

This paper cites LASER: LLM Agent with State-Space Exploration for Web Navigation.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning LASER: LLM Agent with State-Space Exploration for Web Navigation

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.457080Z digest=sha256:acb7d7bec327c9abe4e72ea09eef1677f08270568441ca1b24d0bb9977c0adf0

Observation 67007de0-b117-4a67-a764-1da794453828 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.596124Z digest=sha256:b08e5b21fb2120f17c1a24e33de168a1ac452856ed7b85fd2410a92818efb358

Observation 9b518536-05fb-4fb4-aae4-9fa037557982 · outbound

This paper cites s1: Simple test-time scaling.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning s1: Simple test-time scaling

Reference 25

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unresolved
no resolver link, observed 2026-08-07T13:01:22.713507Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.713507Z digest=sha256:5f5634cab0cfcdfbde86765366cf31009e7a13357ccd4d0f9d14ad865750c924

Observation 83a9e7f2-1d7f-4b33-96f3-481373a19201 · outbound

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

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning WebGPT: Browser-assisted question-answering with human feedback

Reference 26

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unresolved
no resolver link, observed 2026-08-07T13:01:22.826852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.826852Z digest=sha256:147153ebb7017145f7151bb906062337407a893bd580a278d688b9d3119c33ed

Observation f4825587-3a7f-4bc0-976e-06fd526f37c9 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:27.380947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:22.893349Z digest=sha256:93f1d591359077f56f1e116c3f01e54bf16b490f465825400b3fab11d5cc8447

Observation 12d7c553-52f3-46d0-81d4-e8ea9dafa983 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 28

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raw_fallback, observed 2026-08-07T13:01:27.223706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:22.989790Z digest=sha256:4f4e88017f018f6a626efc15b185e46ee88030ccebb779815b5c982bbc6b0230

Observation 945135ee-9b28-4163-86b4-0b92a3c8fe41 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-07T13:01:27.023101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:23.100271Z digest=sha256:6857c8c12e311cdadb1b7bbc09e681766500b0f7778d2123ddfa11cd71a268b6

Observation 0d76ac06-0f6b-468c-9f6c-137e27ee6005 · outbound

This paper cites Autonomous Evaluation and Refinement of Digital Agents.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Autonomous Evaluation and Refinement of Digital Agents

Reference 30

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no resolver link, observed 2026-08-07T13:01:23.261317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.261317Z digest=sha256:23d1ebc6c01f478f0c8113f9e390a85a2e1b130f0e9f787c54578ee89b3b31f9

Observation 63dfd185-4092-4c15-997a-74ee35241cf1 · outbound

This paper cites WebCanvas: Benchmarking Web Agents in Online Environments.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning WebCanvas: Benchmarking Web Agents in Online Environments

Reference 31

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no resolver link, observed 2026-08-07T13:01:23.366902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.366902Z digest=sha256:2ff4b158f5a7cd7e8bf39178c904e2312272f9e9c77f9c74f4b40a0f2cdae44a

Observation da49da50-7f77-48e0-8e68-bb3df4780cf2 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:26.840084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:23.452456Z digest=sha256:0347c65fc64a2fa20f663853c982c8c84e8452d1d6c36dec0b2e1875fb6ec69a

Observation dbc72f20-ca55-4d15-af67-e673b2f1ff4f · outbound

This paper cites ToolRL: Reward is All Tool Learning Needs.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning ToolRL: Reward is All Tool Learning Needs

Reference 33

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no resolver link, observed 2026-08-07T13:01:23.554145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.554145Z digest=sha256:47af14bf1485098bb830c7311cd587ed0733d407bd4b58381afcf81503b78e40

Observation 72453d07-1e30-4f0e-8792-46d2b5fe212c · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-07T13:01:26.699032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:23.664870Z digest=sha256:b488152a284874d1cccc2b804bf192f3c889e4829acb5ae58516c0300bb0a602

Observation c73efc34-93f3-4204-b6af-ed3bbdee65c8 · outbound

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

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 35

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unresolved
no resolver link, observed 2026-08-07T13:01:23.720922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.720922Z digest=sha256:7970fa7021f5d82e9feadf95d8eb81c5e6baef58357b14ffa6d6520367c60d98

Observation 46d2388d-2d3d-4ce4-bd7b-cc6325a520cb · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning HybridFlow: A Flexible and Efficient RLHF Framework

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:23.800865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.800865Z digest=sha256:ff37741477e9f7e46f0ea2a51923271462b01d979a0f38d3ebabe6fb8f3e6e24

Observation 02dc13a4-91d7-46d5-aa79-4997c9059013 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:23.909056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.909056Z digest=sha256:34ab5b08cb98acd81dd34c703b2aac7c3f5b93f341aa3f12a48b3336e51e893c

Observation 6cf7d8cc-a877-4e04-95a5-beb079905529 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:23.985552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.985552Z digest=sha256:42e0bb23dc00690d7e92b44805bc05a4a524f3d5134afc555e107872f8b0e3d1

Observation 6f9d5973-3f37-4027-99f3-391fb6525e4c · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:26.512551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:24.088216Z digest=sha256:7d954d5759d1ec3127945f8cbd87749d9fb335114a32660cfd1918a6f9a45f2c

Observation 3afd9b5f-3988-417f-bb44-1cd1a5b200a8 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:26.316314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:24.193795Z digest=sha256:5ac6f43c4eac31c9b12246092e362a4495a79fcd62c2b2b87c6379d5f9d35261

Observation 8e3605c6-8824-497f-b3e2-91711b2ce922 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.249896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.249896Z digest=sha256:602906c7b0127141b7a00a1927b5838c84d2041e228826b5effadc818c978ad2

Observation 1973b9e9-7deb-4ffe-9ccf-5fb05d9dcecd · outbound

This paper cites RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.323615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.323615Z digest=sha256:75946b72b0354a1e5bf3bcc494aede50d72e88d7c589624fc687995bbade93e0

Observation 47af6178-9d8f-4070-8a8d-64b8fe54ba03 · outbound

This paper cites TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.423383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.423383Z digest=sha256:33ce0b72cb82db1417a1fd59e5a08f14170e9e37de02c59a5c469145c7b7dd94

Observation 148e3680-84c5-44c1-aba5-a5839a598083 · outbound

This paper cites Qwen2.5 Technical Report.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Qwen2.5 Technical Report

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.515562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.515562Z digest=sha256:1382880fd2fd850252f063b5f34edb520aa5d92fa2897337793d1c6faae5ad72

Observation 70230196-de45-4987-ba2e-0feb2d3e5680 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.584038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.584038Z digest=sha256:8687a42ea3e55da47a04d3d819f5c78d31ecfe8a01111165f4ad40919f76f06f

Observation cbafc01e-53ce-4ff1-b7c3-a0d2912c1ecd · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.656432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.656432Z digest=sha256:6a56face6665c306f7db4740b25a4b4bb1e963a1f8a735b08c2a814dbb579dfc

Observation c435f826-8d81-4429-85f1-58a81941880e · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.740668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.740668Z digest=sha256:64a3f08bfa01a25406d14704422a89f7579745b631819ed359363c259e16f7e0

Observation 76fe97b0-2dcd-4329-a6e2-899f652b19cf · outbound

This paper cites AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.836115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.836115Z digest=sha256:c7d8caa08d722da42b49b1f1ad5d5a28483fa48af61663ba688f7c20f7631445

Observation a9d98500-5871-425b-8269-0adb0b2176f0 · outbound

This paper cites GPT-4V(ision) is a Generalist Web Agent, if Grounded.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning GPT-4V(ision) is a Generalist Web Agent, if Grounded

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:24.921010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:24.921010Z digest=sha256:e62129f277c8845a28b0082f53451f2ea12698c0b24c008d6ce9ce70de02ed4f

Observation d1f95386-dd9e-4eb1-a2a0-bc0118ab9296 · outbound

This paper cites WebArena: A Realistic Web Environment for Building Autonomous Agents.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:25.009096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:25.009096Z digest=sha256:01f949b5fd4c8d2e7c90cb4f99d67ba6339e2961fce3700bf7bbb00c72ac6be0

Observation d7b712e4-e754-4120-836e-84c908bc680b · outbound

This paper cites Rossi, Somdeb Sarkhel, and Chao Zhang.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Rossi, Somdeb Sarkhel, and Chao Zhang

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:01:26.145194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:25.083595Z digest=sha256:199588d1f7787823ca5a62aa63142be09c5e0681b14c6db1153be8c47ed401e0

Observation 65f17232-ffc7-4b7c-8295-3501c40d7130 · outbound

This paper cites an unresolved cited work.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:01:25.939759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:01:25.203793Z digest=sha256:ec2d81bd0312e0847fed05a3ec414b1f30a4d5784f74eca8b99d250cd5ddc079

Observation 99e6c23d-c187-416f-b266-476e79738164 · outbound

This paper cites Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training.

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:25.268734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:25.268734Z digest=sha256:0ed707b1726fe69934a2e4e4b16e70dbf942d2f736459c0a1531786235f277ad

Pith citing papers

Observation 0c5f77f0-f1c3-468c-9463-1310ddc94d86 · inbound

DynaWeb: Model-Based Reinforcement Learning of Web Agents cites this paper.

DynaWeb: Model-Based Reinforcement Learning of Web Agents WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:37:41.946935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T09:33:30.444057Z digest=sha256:e6582f5a7e5b0160453a02f9eedae80b86e5aac112904553f32e5c4618f99497