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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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=sha256:4341097540df4addec4cae409648e50d47345d9315e662fbfb7950c521e0ad5b

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:bb0e09d3baf1b2bf6e8d79f10588329b29ca7864ba4b07e9e133f0a4d8910173

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:c6844a75df5a45716442e519f13468c2c3ba88207a9fb0f363d5cba7aeb15497

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:b9e4880daf618eb7292b011950c719a0a2efcafa3752bb25c9c56b39f08179cf

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=sha256:31b8310e23c9be8289817b7238305c9fc72428f3d7bbe378d5e2495d63db4aca

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:20.888771Z digest=sha256:43485630dc2429d45f4b87e87fc37f621012126dbe6de1c4e24ac1cf34434b3d

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:20.987141Z digest=sha256:4907c0a61aa57a67e59d1be7ac1815be2dc7691af5b28e47ebce39427ba54f2b

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=sha256:158c053f194aeb2b367a6ba866fa9250f46ccd6c00b5f6f00d26984715fc8544

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:21.126022Z digest=sha256:0697d40a5d0e9adf5a070cd1d9dbdea4e0550a0a58bbe494dafc8bd4f55f88be

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:f8233fc84070e6da16348a902efc8681a610a1c01f12b1d5d7064e23b87228ec

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:d0cb1a3a3473601589ce3f2bc5d5d3edd4a7033b9e8b433cc85f044db3bf5694

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=sha256:3e0ad3c26ea462ee2fb8f7453649fdf838d980f17d7b6b372b41e3c6621f51ef

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

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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=sha256:3ef960fae637395251eba11f3cfaf0760e9c2ef9f8502c10b0c434a34f3e0d0a

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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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:c9e30214ae75ec70b80a30e9a77d43f77435856cbb6462648a954a98cda708ba

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
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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=sha256:4463400a2dae08f1de8aa9cb46d69c74592e9160d5ebfbc83c14f377130a7672

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
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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=sha256:64dd2086a2a36e9ab0865c11f0ded5e9db35d5d39239bbf47e2bdc7a63f5200f

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:21.867543Z digest=sha256:d089bbac1ee3bb05a1fe52a4cfaaab7fafb75e976b8f2a76810b554c2dc40ccc

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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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=2026-08-07T13:01:21.945890Z digest=sha256:57ab321b917c972ef2805aec5a3c4e71eca68d0d5f838181b04bb5f477891ce4

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:a8f43132be90a0cd9f9c0e806b775e7554108970acb4be32f39a37b72ff7ed28

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=sha256:03edc6ac3f685308f7f0ce194885412b6ebdb180e018385ae6e863c58c9bcf8a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.236158Z digest=sha256:1ffaed18a82a318f488f0b80a80474befb684c87b5a6ffbf10aa6128b79c76a7

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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source=arxiv_source observed=2026-08-07T13:01:22.351667Z digest=sha256:0d96f1823fd22dea36a3c47bdbc1392a40398a569b6505a8bc067c9b7756c392

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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source=arxiv_source observed=2026-08-07T13:01:22.457080Z digest=sha256:858a3dd3b5b3693f2e110aad4e5311903bfdf31692fa3248e76b5c32dda27269

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.596124Z digest=sha256:fcdad3a4f99086923eb6fb266a2fdcff49e398bc1f77eabd7821c92e2a36c242

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:22.713507Z digest=sha256:f8770be41e9bd83bd5c99cd1c20a5f159472f49322293dc5bc2dee71ebc6d1c2

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=sha256:8e59f682f5ec34fb50fe5d6a8e07515f22301b6c8e7ec153852830613b47bc1b

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:22.893349Z digest=sha256:53c6cc05329b6b0f66944216947f77b22e2edbff4864c8cfd47eb464d9947cd5

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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unresolved
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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:22.989790Z digest=sha256:664949d6b1b60f4c24aba8b8d62dbfb1c0f59defad81daf75dcb4e57f2478097

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:23.100271Z digest=sha256:ea97613afe397029fb02211b611c86ac3ecfffe86573534fa7e979652bb7e8be

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=sha256:48fb9df33e09782a1fe96083d6eb9c95b6446ce882b2f27abb4033008d46f419

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.366902Z digest=sha256:166e6fa69cf58f0e8a662ff943cfb3a25c8ae0b02df54ee07a2a1a7b046ff85a

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:23.452456Z digest=sha256:c70677720885888ca63a826368f8de3c65df6bc147fdfa7c8ce3c74eea6c22fd

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:01:23.554145Z digest=sha256:be2fc03fecd299bc4424baab48af22cb4ebd74ae921e3c35a38655c26650cc2c

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:23.664870Z digest=sha256:1ad3840ea9bcaec7453b2cf5cef86b50ed002e8d4a91870774c5c3b56d9ca127

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:fc9c56aac4b29bd37422db8f8641eae569dfc0c783b7a0ef5a1aa4dae09b4a28

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=sha256:51a7bb7032841731ef95bd3352338cabc97c1106cdc7295177448ac8fa8afd1c

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=sha256:1491bb642b57b0bdbbc04992323c44e7f2131b70e5a28328016f65803690f0d0

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:d0af702b09ab14593e720dc41276baced55b323523e2b231cb513ed710de1d49

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:24.088216Z digest=sha256:565c585125ff4cb89c63c7df46e285fe1e344ab85db596a7671e4781acf4deb8

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:24.193795Z digest=sha256:311210eb2ab7410e9483a76d9ca61f7f46efe37f5611e11f81cdd45f29cbb104

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=sha256:36543bc30097396cccf5fd218d78f299cc0e44ff9e76f50cc0a53feca6912d58

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:f61f58124fa27ee1c8a064ed506e0b4c40260b6fc0737327dc7dc9ae6b0c840f

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=sha256:41104812406a7c34446c217b4dd182b9795854c4a3c42ae7eea04ddf87a92539

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=sha256:1158d7081cfd2903eef8604973999980f4483e733583bc9c75863d1a2a4f13cf

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:c219b5c6e8ec6f72541abc7e3aaa4f1a623d0d0f9f40764f9c5e59745b5fe06c

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:ca8e6164aebc65c7da65d16d563859e6c4af1728e6a56cc53ad33f3f90ace0a6

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=sha256:1deedd292945d0d4308ef6f3da5a9e4456f24486ecfff10a8e936ba94a890d79

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=sha256:69f4cfec5b5f3d90921ee14661ad7bf02f8a7ee81d7054441b1673bcd9812515

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:f21d3dcc2b0de3f3329a88c302abe0a464c721e3be4beb980145a47fcdd29397

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=sha256:7dd96046b8af02b2a50b1c10bb10a2b98a626bba772ade073467fce8b0a187cb

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:25.083595Z digest=sha256:34be6d2f3926ad8e8a9204c62d33dd1c80946c39571a6a9df89fb2bd0560232d

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T13:01:25.203793Z digest=sha256:f90bc250ac371cf2fec36076d1adb2a0aa91b28ff0b2979f291738ea1d031396

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:c82f40e64d32e0b1696b549a595a5ea85079031afe6eedf0b9e290d05d5eeeaa

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T09:33:30.444057Z digest=sha256:1a7d5c8447dc8cb3535549f8fd5fd1df44e179e6372879877a68679fce0b9709