Paper Citation Record · LEDGER

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

As of 16 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 17 inbound Pith citation observations for arXiv:2505.16282.

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

pith.paper-citation-record.v1
2505.16282 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:07:10.796768Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:19:15.434119Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:00:08.408321Z

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy5
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a97a4621-6c2e-4838-8b44-aac68c14df56 · outbound

This paper cites Qwen2.5-VL Technical Report.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Qwen2.5-VL Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:08.732949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5544cf9-7703-4840-aa66-c648472154de · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:08.818285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06a674f1-8a7e-48ab-8c65-6f05654887e2 · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay KTO: Model Alignment as Prospect Theoretic Optimization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:08.943210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a204acfe-dfc4-4120-a7ae-98cec497d88e · outbound

This paper cites Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.054423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96a71639-ea78-4543-8235-922a76b611cc · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.148499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2923ec7-65ca-4e66-a110-9ab98fa6804c · outbound

This paper cites Cogagent: A visual language model for gui agents.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Cogagent: A visual language model for gui agents

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:11.440915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 08626187-7624-473a-848e-7420015aef08 · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.358618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48d13b54-9277-4d20-9f3b-7d8563c4eae4 · outbound

This paper cites OpenAI o1 System Card.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay OpenAI o1 System Card

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.452790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b5481a0-74d7-401d-881c-9dac23cee2e4 · outbound

This paper cites OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.526745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0a72d0c-1f2b-439e-b76a-0815a1f77501 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Efficient memory management for large language model serving with pagedattention

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:11.374189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 723a7e63-be07-4902-9360-6ab11888e498 · outbound

This paper cites Code-r1: Reproducing r1 for code with reliable rewards.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Code-r1: Reproducing r1 for code with reliable rewards

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.737013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ea43a1d-8027-47f5-b596-6acbc00c0eb8 · outbound

This paper cites Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.853262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc7d8539-4150-48cb-832c-6b4548dd2e82 · outbound

This paper cites Decoupled Weight Decay Regularization.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Decoupled Weight Decay Regularization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:09.981894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a897a41-6265-4c2c-abd7-a4289024e73f · outbound

This paper cites ScreenAgent: A Vision Language Model-driven Computer Control Agent.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay ScreenAgent: A Vision Language Model-driven Computer Control Agent

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.028219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53b21184-ee19-4e15-a7de-b8d3d4fa34d7 · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay ToolRL: Reward is All Tool Learning Needs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.067180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 202e5032-e30c-4814-905a-6ed48af0b141 · outbound

This paper cites UI-TARS: Pioneering Automated GUI Interaction with Native Agents.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay UI-TARS: Pioneering Automated GUI Interaction with Native Agents

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.120332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15b11a46-da31-4f47-aea5-c4c68fc8cadd · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Direct preference optimization: Your language model is secretly a reward model

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:11.288367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1f8adde8-ef64-4dfe-a2b9-59b519a037ef · outbound

This paper cites Proximal Policy Optimization Algorithms.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Proximal Policy Optimization Algorithms

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.211575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d28fa66-0dad-4959-9ec7-efc2a223b9c2 · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.279353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 440ba8ab-3650-4f73-bf52-0b10af21267c · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay HybridFlow: A Flexible and Efficient RLHF Framework

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.332778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ababca5-5736-47a2-924b-fd00f9d5b887 · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.363216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda3ee73-fe85-4711-a4cc-bec481c35515 · outbound

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

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Chain-of-thought prompting elicits reasoning in large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:11.194077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8f180272-3fd7-41f7-af45-ed5731c23050 · outbound

This paper cites OS-ATLAS: A Foundation Action Model for Generalist GUI Agents.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay OS-ATLAS: A Foundation Action Model for Generalist GUI Agents

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.444576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58f4df80-56d4-438d-8f34-5af8fc91a67a · outbound

This paper cites GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.491309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4d6f9ea-76b2-4537-a06c-9ecfa4747bd3 · outbound

This paper cites Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:07:11.128405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ca674936-63b4-4926-aa11-f4c6420fc5b6 · outbound

This paper cites Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.588099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a363f308-e927-4e0c-9fbf-e202d39c717e · outbound

This paper cites Aria-UI: Visual Grounding for GUI Instructions.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay Aria-UI: Visual Grounding for GUI Instructions

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.649086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9423a99-3bc6-4f52-a8cb-ee85a07db547 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.758735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b169f929-fb11-4c83-8be7-a284473d8032 · outbound

This paper cites SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks.

ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T15:07:10.796768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c7df2476-8c0a-48d9-8a9f-2cf60b09acd7 · inbound

MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment cites this paper.

MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:14.276099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efa7606d-90a1-4c89-a24d-f755e76324f5 · inbound

UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning cites this paper.

UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-13T10:13:59.047730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0acd32bd-456b-4de0-87eb-b50696880523 · inbound

Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning cites this paper.

Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T12:52:27.271355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c88db6-3fd5-4294-852b-ee3cc6395ca1 · inbound

AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning cites this paper.

AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T16:30:39.322149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7a6fa83-59c1-42f8-bd82-ecc76dcd26e5 · inbound

Agentic Reasoning for Large Language Models cites this paper.

Agentic Reasoning for Large Language Models ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-17T15:14:25.866371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a00a8d54-94c6-4eff-8a4b-afedab8048e3 · inbound

Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization cites this paper.

Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:36:35.212903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 32ddfcb8-f0f4-4f19-ad06-b0543b4f3018 · inbound

Faithful Mobile GUI Agents with Guided Advantage Estimator cites this paper.

Faithful Mobile GUI Agents with Guided Advantage Estimator ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:41:24.147115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3ab69e72-872e-4417-b40f-66d6b72ad9eb · inbound

On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length cites this paper.

On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 66

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:40:40.641959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 61a0ea97-88b7-4880-83e2-222fca09fa1a · inbound

Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization cites this paper.

Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:01:17.873771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e43a52a5-801e-44c0-a4e7-1f00e7d6cdf0 · inbound

Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization cites this paper.

Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:17:07.683646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 494b1bdb-c798-4aa8-b384-8e948dd3bd4f · inbound

ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents cites this paper.

ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-13T03:52:12.365420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ad7335ec-cd17-4d1b-85cc-f1e71fcfc475 · inbound

RLVR without Ineffective Samples: Group Prioritized Off-Policy Optimization for LLM Reasoning cites this paper.

RLVR without Ineffective Samples: Group Prioritized Off-Policy Optimization for LLM Reasoning ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:13.369302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 44daa594-25cc-420c-a599-f689908c2cdb · inbound

StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents cites this paper.

StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:47:09.594291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 46e7f937-ef14-4065-9ae5-ae9c9c4aa368 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 125

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:09:40.731617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3450fa5e-24d1-467e-99a6-dbf7f0c44049 · inbound

Learning with a Single Rollout via Monte Carlo Pass@k Critic cites this paper.

Learning with a Single Rollout via Monte Carlo Pass@k Critic ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:00:08.409789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 490492e7-74a4-411e-afa8-b66bcd8c2a8d · inbound

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents cites this paper.

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T12:53:26.532661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6632b7f6-e440-45f9-bf76-c7f0b764d1da · inbound

Software Engineering for and with GUI Agent cites this paper.

Software Engineering for and with GUI Agent ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

Reference 137

Resolution: unresolved; no resolver link, observed 2026-08-11T20:19:15.434119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.