Paper Citation Record · LEDGER

Large Language Models Can Self-Improve At Web Agent Tasks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2405.20309.

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

pith.paper-citation-record.v1
2405.20309 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:24:50.385849Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:58:02.913639Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0a7fb9ba-df97-4fc1-9ade-367acd1a7d3a · inbound

InSTA: Towards Internet-Scale Training For Agents cites this paper.

InSTA: Towards Internet-Scale Training For Agents Large Language Models Can Self-Improve At Web Agent Tasks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T14:24:50.385849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b89e509-7c29-40a5-b8b4-05a4e0deaacf · inbound

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks cites this paper.

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks Large Language Models Can Self-Improve At Web Agent Tasks

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-17T21:32:18.616934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 66c78cd0-d75e-40b0-99a7-4be695aa177d · inbound

Build the web for agents, not agents for the web cites this paper.

Build the web for agents, not agents for the web Large Language Models Can Self-Improve At Web Agent Tasks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T04:17:00.752451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d9105ce-bdcd-43d4-a397-abfbbd758ab0 · inbound

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges Large Language Models Can Self-Improve At Web Agent Tasks

Reference 288

Resolution: unresolved; no resolver link, observed 2026-08-06T14:13:07.312181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deb52c15-8308-4915-a97d-d826bbc120e8 · inbound

Morae: Proactively Pausing UI Agents for User Choices cites this paper.

Morae: Proactively Pausing UI Agents for User Choices Large Language Models Can Self-Improve At Web Agent Tasks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T14:22:45.707874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48a6a741-1dff-4fab-8460-5402bd2a60b7 · inbound

Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective cites this paper.

Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective Large Language Models Can Self-Improve At Web Agent Tasks

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:55:33.423781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9a2aef0-bf12-426c-947e-c2329229fb8d · inbound

Compute-Accuracy Pareto Frontiers for Open-Source Reasoning Large Language Models cites this paper.

Compute-Accuracy Pareto Frontiers for Open-Source Reasoning Large Language Models Large Language Models Can Self-Improve At Web Agent Tasks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T13:19:47.781489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9cd0f58-025a-4732-a328-5c071f1928f1 · inbound

Rethinking Token Pruning for Historical Screenshots in GUI Visual Agents: Semantic, Spatial, and Temporal Perspectives cites this paper.

Rethinking Token Pruning for Historical Screenshots in GUI Visual Agents: Semantic, Spatial, and Temporal Perspectives Large Language Models Can Self-Improve At Web Agent Tasks

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:03:20.120806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 39fcd71e-5726-4e3b-9540-c6b334fc200d · 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 Large Language Models Can Self-Improve At Web Agent Tasks

Reference 286

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:58:02.915043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 15964e59-f02a-42c4-85d8-0bad85c80133 · inbound

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills cites this paper.

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills Large Language Models Can Self-Improve At Web Agent Tasks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T04:28:47.436292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.