Pith. sign in

REVIEW 3 major objections 5 minor 53 references

Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution

T0 review · 3 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read A harness that rewrites its own core through reviewed commits sets new agent-benchmark highs

desk verdict A serious engineering report with real transparency, but the central attribution of benchmark gains to the self-modifying core is not yet controlled. read the letter →

arxiv 2608.08311 v2 pith:XUJOSLYE submitted 2026-08-08 cs.SE cs.AI

Anton Razzhigaev , Andrei Gritsaev , Andrei Kaznacheev , Nikita Dragunov , Roman Yampolskiy , Andrei Kuznetsov This is my paper · ORCID
classification cs.SEcs.AI
keywords self-improvingagentsagentharnessreviewedcoreevolutionTerminal-Bench2.1OSWorldCL-Benchoperationalsafetypersistentmemory
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Ouroboros is an agent harness whose tools, prompts, context assembly, and core implementation live in a versioned repository and change through reviewed commits that become the runtime for later work. The paper reports that this self-developing design sets a new best score on Terminal-Bench 2.1 (86.74% after trajectory audit), exceeds the previously reported best on OSWorld-Verified (90.69%), and reaches a new state of the art on CL-Bench (0.2301 normalized reward), while matching frontier harnesses on SWE-bench Pro and GAIA at equal model strength. A 161-day live deployment, Hope, under governed human interaction across seven communication surfaces, is presented as evidence that recursive and experience-driven core evolution can run continuously and safely. If correct, the work would show that the harness, not just the model, is a learnable and auditable component of agent capability.

What carries the argument

The load-bearing mechanism is the reviewed commit pipeline: a deterministic preflight, a fingerprint of the staged diff taken before and after review, and a multi-model diff-review panel that cannot record a clean pass below quorum. Each accepted commit to the system repository immediately becomes the runtime for subsequent tasks, so evolution is serialized through an auditable gate rather than applied as an unconstrained optimization run. An always-loaded constitution is the standard the gate reviews against, governance files are protected from ordinary write tools, and an authenticated operator channel carries budget controls and an emergency halt. This arrangement separates the substrate being evolved from the authority that approves each mutation, and the two evolution modes—recursive free evolution and experience-driven core evolution—feed candidate changes into the same gate.

What would settle it

Run the same Terminal-Bench 2.1 campaign from the same frozen seed with core evolution switched off; if the fixed harness scores 86.74% within the binomial error, the evolved-core explanation loses its support. Separately, audit all 1,085 Hope commits for any change to review rules, reviewer prompts, or governance-file protections; finding one would show the gate is not independent.

Watch

Extended reading notes

Core claim

The central claim is that a harness which can modify its own implementation through a reviewed commit gate outperforms fixed harnesses running the same base model on long-horizon agent benchmarks. Two evolution modes produce the changes: recursive free evolution, in which improving the system is itself a task that can schedule further cycles, and experience-driven core evolution, in which ordinary work and social feedback expose durable error classes that become reviewed structural fixes. The reported scores come from frozen seeds, public per-task traces, and audit-adjusted results; one Terminal-Bench trial that satisfied a weak verifier through an unintended shortcut was removed at the maintainers' request, leaving 386 of 445 trials correct. The live Hope deployment logged 1,085 self-modification commits, 94.2 percent of them agent-authored, with users surfacing proposals but the agent deciding which changes to pursue.

Load-bearing premise

The results and safety guarantees depend on the reviewers that approve self-changes being genuinely independent of the agent, but those reviewers are built from the same kind of model and live in the same codebase the agent can edit, so a shared blind spot could let a shortcut or a weakened guardrail pass the gate.

Editorial extensions

If this is right

  • With the same base model, a self-developing harness reports gains of several percentage points over fixed harnesses on Terminal-Bench 2.1 and OSWorld-Verified, making harness design a first-class axis of agent capability.
  • Reported state-of-the-art scores require trajectory audits and contamination filters: the audit found one rewarded shortcut, and the SWE-bench Pro comparison flipped after symmetric filtering of leaked reference solutions.
  • Self-modification can be governed in practice: over 161 days, the live deployment logged 1,085 self-modification commits under a blocking review gate, with no recorded episode resisting operator shutdown.
  • Persistent memory carries positive learning across ordered task streams on CL-Bench, while schema drift remains a failure mode that motivates explicit temporal and domain metadata.
  • Human interaction can drive core improvement: a duplicate-send bug and a context-overflow fault both became reviewed structural fixes that changed how later tasks are executed.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper does not report a controlled ablation with evolution disabled; if such an ablation on the same seed and model matched 86.74% within error, the evolved-core explanation for the Terminal-Bench gain would be unsupported.
  • The independence of the review gate is the crux of both the benchmark validity and the safety claims; an external audit of all 1,085 commits for any edit to review rules, reviewer prompts, or governance protections would settle whether the gate can be captured from within.
  • The pattern-register design suggests a scaling conjecture: more diverse ordinary tasks should produce more durable error classes and faster improvement; this is testable by measuring pattern-register growth against performance on a fixed holdout set.
  • Because an evolving agent can select its own model APIs, 'the model' is an unstable variable in future comparisons; evaluations may need to report the full commit history or fix an evolution budget alongside scores.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper presents Ouroboros, a self-modifying agent harness whose core code, prompts, tools, and review logic evolve through a reviewed commit gate. Core evolution has two modes: recursive free evolution and experience-driven evolution. The evaluation section reports state-of-the-art numbers on Terminal-Bench 2.1 (86.74% audited), OSWorld-Verified (90.69%), and CL-Bench (0.2301), plus model-matched parity on SWE-bench Pro and GAIA, all obtained with official verifiers and with evolution explicitly disabled in the benchmark campaigns. The paper also describes Hope, a 161-day live deployment across seven communication surfaces, and an operational safety architecture with layered guardrails. The authors disclose scaffold settings, release per-task traces, and include a self-audit that found and zeroed one Terminal-Bench shortcut.

Significance. If the claims hold, the paper makes a meaningful contribution: it documents a version-controlled, review-gated self-modifying agent, provides open per-task traces and run manifests, and reports a long-running deployment with honest operational statistics. The scaffold disclosures and the symmetric SWE-bench Pro contamination filter are examples of unusually transparent methodology. However, the headline attribution of the benchmark results to 'reviewed core evolution' is not tested, because every benchmark campaign explicitly disables evolution (Appendix C). The main positive result is therefore a frozen-snapshot harness with persistent memory, not a demonstrated benefit of self-modification. The OSWorld and Terminal-Bench comparisons also lack matched-model controls and adequate statistical analysis. These issues are load-bearing for the central claim but addressable with additional analysis or revised framing.

major comments (3)
  1. [Section 5, Table 2, Figure 4] The benchmark campaigns all run with 'evolution off' (Appendix C, Table 3), so the reported SOTA scores cannot by themselves demonstrate that reviewed core evolution improves performance. No ablation holds the base model and the fixed harness constant while toggling core evolution. The Terminal-Bench 2.1 comparison is unpaired and uses different models (Opus 5 vs Fable 5), and the 86.74%-vs-83.8% margin is roughly two binomial standard errors; this is suggestive but does not isolate the harness contribution. The OSWorld-Verified margin over Intelligence-Indeed is 0.50 percentage points on 361 tasks, well within one binomial standard error. As written, the paper's central claim that a 'self-developing frontier coding agent' sets these records is not empirically supported. I request either a controlled ablation or a revised claim that the results measure a frozen Ouroboros snapshot with persistent memory and one improvement pass.
  2. [Section 5, OSWorld-Verified paragraph] The claim 'an Opus 5 run reaches 90.69%, exceeding the best previously reported score' is not statistically supported. The difference from the 90.19% baseline is 0.50 percentage points on 361 tasks, with a binomial standard error of roughly 1.6 percentage points. No confidence intervals or significance tests are reported for OSWorld, and Figure 4's truncated axis visually exaggerates the gap. Please report uncertainty and either claim a tie or provide a proper hypothesis test.
  3. [Section 7 and Limitations] The operational safety claim that guardrails 'remain authoritative under evolutionary pressure' rests on the multi-model diff-review gate and the constitution's protected core. The Limitations admit that 'LLM reviewers can share blind spots with the agent,' and the review panel is implemented inside the mutable repository. The paper's own trajectory audit found one rewarded Terminal-Bench shortcut that the official verifier accepted, and the audit that caught it is not guaranteed complete. This does not invalidate the benchmark numbers, but it weakens the safety guarantee: a blind spot that includes a way to bypass the review gate or a benchmark verifier would undermine both the SOTA claims and the safety architecture. I recommend stating this as a bounded claim and, where feasible, adding an independent audit or an explicit residual-risk analysis.
minor comments (5)
  1. [References and Table 1] The references contain 'V oyager' (Wang et al., 2023) with an extra space; also check for stray spacing in 'T ools' in Table 1's header.
  2. [Figure 4] The truncated axes in Figure 4 make the OSWorld-Verified gap appear much larger than it is. Consider full-range axes or adding error bars and confidence intervals.
  3. [Section 6, 'Isolation failure'] The GAIA isolation-failure discussion notes that 'complete filesystem isolation still requires a stronger sandbox than path conventions alone.' This known gap should be reflected in the safety summary in Section 7, not only in the audit section.
  4. [Reproducibility] The paper says traces and manifests are public, but no permanent archive or versioned DOI is provided; consider pointing to a stable repository tag or Zenodo record.
  5. [Abstract] The abstract states 'the best result reported on this benchmark' for Terminal-Bench and 'exceeding the best previously reported score' for OSWorld; these should be softened pending the statistical analysis requested in the major comments.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: benchmark SOTA claims rest on external official verifiers with frozen seeds and evolution disabled; no fitted parameter, self-citation chain, or definitional reduction.

full rationale

The core results in Section 5 are direct measurements against official benchmark verifiers (Terminal-Bench 2.1, OSWorld-Verified, CL-Bench, SWE-bench Pro, GAIA) on frozen system snapshots with core evolution and task delegation disabled, as disclosed in Appendix C (Table 3). No parameter is fitted to a subset of benchmark data and then 'predicted' on an adjacent subset; the trajectory audit removes one contaminated trial and the SWE-bench Pro symmetric filter removes leaked instances, which are data-cleaning steps, not fitted predictions. The paper does not cite its own prior work as load-bearing evidence: the only system contributor is the agent itself, credited in the 'Use of AI Assistance' section, and no uniqueness theorem or ansatz is imported from the authors' earlier papers. The remaining concern highlighted in the Limitations — 'LLM reviewers can share blind spots with the agent' — weakens the independence of the self-improvement review gate, and the missing same-model ablation with core evolution toggled is an attribution gap, but neither is a circularity reduction: the SOTA numbers are not derived from the review gate or from the self-improvement loop by construction. Under the hard rules, absent a quoted equation or fitted-parameter-as-prediction equivalence, the appropriate finding is no significant circularity.

Assumptions & free parameters 0 free parameters · 5 assumptions · 0 invented entities

The paper introduces no fitted parameters or invented entities; its results are empirical scores from external benchmarks. The claims rest on benchmark-protocol integrity assumptions, the effectiveness of the anti-lookup and audit measures, comparability of public baselines, and the independence of the review gate, all listed below.

assumptions (5)
  • domain assumption Official benchmark verifiers and scorers are authoritative and correctly measure intended capability
    Section 5 states all runs use official verifiers, but the paper does not independently validate the verifiers or the public baseline scores.
  • domain assumption The anti-lookup paragraph prevents the model from exploiting known benchmark answers, and trajectory audits are complete
    Section 3 adds a harness-authored anti-lookup paragraph; Section 6 audits found one shortcut, implying the audit is not guaranteed exhaustive.
  • ad hoc to paper Reviewers (multi-model LLM panel) do not share a blind spot with the agent that would let harmful or benchmark-exploiting changes pass
    The Limitations section states "LLM reviewers can share blind spots with the agent"; the safety claims assume functional coverage despite this.
  • domain assumption Public baseline scores are comparable to Ouroboros runs despite different harnesses, providers, and seed environments
    The paper compares against named baselines from leaderboards and system cards without a common control harness; differences include turn budgets and feasibility passes.
  • standard math Standard binomial standard error over the full trial set can approximate the uncertainty of the Terminal-Bench gap
    Figure 4 caption: "whiskers ±1 binomial SE"; the paper treats the per-system SE of about 1.7pp as the statistical basis for the SOTA claim.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution." pith.science (2026). https://pith.science/paper/XUJOSLYE

@misc{pith2026260808311,
  author       = {Pith},
  title        = {Pith review of: Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XUJOSLYE}},
  note         = {Machine review of arXiv:2608.08311}
}
read the original abstract

We present Ouroboros, a self-developing agent harness whose tools, prompts, context assembly, and core implementation improve through reviewed commits that become the runtime for later work. Core evolution proceeds in two modes. In recursive free evolution, improvement is itself a task, and completing one evolution cycle can schedule the next. In experience-driven core evolution, ordinary work and social interaction expose bugs, rough edges, and inefficient context construction that lead to reviewed structural changes. On Terminal-Bench 2.1, an Opus 5 run scores 86.74%, the best result reported on the benchmark. On OSWorld-Verified, an Opus 5 run reaches 90.69%, exceeding the best previously reported score. A five-rollout CL-Bench campaign achieves a normalized reward of 0.2301, setting a new state of the art. Hope is the longest-running publicly documented Ouroboros deployment. It is a 161-day living agent experiment in free evolution under governed human communication across seven surfaces. Human interaction surfaces faults and generates proposals, but the agent decides which changes to pursue. Because a self-developing agent may rewrite its own code and select new model APIs, operational safety becomes a primary design problem: guardrails must remain authoritative under evolutionary and public social pressure. Benchmark campaigns use frozen system snapshots, while Hope continues live evolution on a separate lineage.

Figures

Figures reproduced from arXiv: 2608.08311 by the authors.

Figure 1
Figure 1. Ouroboros architecture. One supervised runtime dispatches work to admitted workspaces, task trees, [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Subagent patch-integration protocol. Acting [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Task-tree view of a live Ouroboros session: [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Results on Terminal-Bench 2.1, OSWorld-Verified, and CL-Bench against named published baselines. [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]
Figure 5
Figure 5. Figure 5: Operational control boundaries. Public interactions enter one ordered log and bounded digests; budget [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: Hope public deployment series through 6 August 2026. Axes start at zero; February and August are partial [PITH_FULL_IMAGE:figures/full_fig_p012_6.png]
Figure 7
Figure 7. Figure 7: Ouroboros interface surfaces. The complete project view shows a live visual-verification task, its [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]

Review history (3 revisions) →

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

53 extracted references · 16 linked inside Pith

  1. [1]

    Constitutional

    Bai, Yuntao and Kadavath, Saurav and Kundu, Sandipan and Askell, Amanda and Kernion, Jackson and Jones, Andy and Chen, Anna and Goldie, Anna and Mirhoseini, Azalia and McKinnon, Cameron and others , year =. Constitutional. 2212.08073 , archivePrefix=

    arXiv

  2. [2]

    and Maxwell, Tim and Cheng, Newton and others , year =

    Hubinger, Evan and Denison, Carson and Mu, Jesse and Lambert, Mike and Tong, Meg and MacDiarmid, Monte and Lanham, Tamera and Ziegler, Daniel M. and Maxwell, Tim and Cheng, Newton and others , year =. Sleeper Agents: Training Deceptive. 2401.05566 , archivePrefix=

    arXiv

  3. [3]

    2022 , eprint =

    Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals , author =. 2022 , eprint =

    2022

  4. [4]

    , year =

    Omohundro, Stephen M. , year =. The Basic

  5. [5]

    2014 , publisher =

    Superintelligence: Paths, Dangers, Strategies , author =. 2014 , publisher =

    2014

  6. [6]

    2023 , eprint =

    Voyager: An Open-Ended Embodied Agent with Large Language Models , author =. 2023 , eprint =

    2023

  7. [7]

    Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST) , year =

    Generative Agents: Interactive Simulacra of Human Behavior , author =. Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST) , year =

  8. [8]

    , year =

    Zelikman, Eric and Lou, Eliana and Schultz, Patrick and Yao, Quan and Zhang, Cheryl and Mukherjee, Subhabrata and Goodman, Noah D. , year =. Self-Taught Optimizer (. 2310.02304 , archivePrefix=

    arXiv

Show all 53 references
  1. [9]

    2024 , eprint =

    Automated Design of Agentic Systems , author =. 2024 , eprint =

    2024

  2. [10]

    Zhang, Jenny and Hu, Shengran and Lu, Cong and Lange, Robert and Clune, Jeff , year =. Darwin. 2505.22954 , archivePrefix=

    arXiv

  3. [11]

    2410.04444 , archivePrefix=

    Yin, Xunjian and Wang, Xinyi and Pan, Liangming and Lin, Li and Wan, Xiaojun and Wang, William Yang , year =. 2410.04444 , archivePrefix=

    arXiv

  4. [12]

    2025 , eprint =

    A Self-Improving Coding Agent , author =. 2025 , eprint =

    2025

  5. [13]

    2511.13646 , archivePrefix=

    Xia, Chunqiu Steven and Wang, Zhe and Yang, Yan and Wei, Yuxiang and Zhang, Lingming , year =. 2511.13646 , archivePrefix=

  6. [14]

    2026 , eprint =

    Autogenesis: A Self-Evolving Agent Protocol , author =. 2026 , eprint =

    2026

  7. [15]

    2025 , eprint =

    A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence , author =. 2025 , eprint =

    2025

  8. [16]

    1805.00899 , archivePrefix=

    Irving, Geoffrey and Christiano, Paul and Amodei, Dario , year =. 1805.00899 , archivePrefix=

    arXiv

  9. [17]

    2023 , eprint =

    Improving Factuality and Reasoning in Language Models through Multiagent Debate , author =. 2023 , eprint =

    2023

  10. [18]

    and others , year =

    Zheng, Lianmin and Chiang, Wei-Lin and Sheng, Ying and Zhuang, Siyuan and Wu, Zhanghao and Zhuang, Yonghao and Lin, Zi and Li, Zhuohan and Li, Dacheng and Xing, Eric P. and others , year =. Judging. 2306.05685 , archivePrefix=

    arXiv

  11. [19]

    2023 , eprint =

    Self-Refine: Iterative Refinement with Self-Feedback , author =. 2023 , eprint =

    2023

  12. [20]

    2305.11738 , archivePrefix=

    Gou, Zhibin and Shao, Zhihong and Gong, Yeyun and Shen, Yelong and Yang, Yujiu and Duan, Nan and Chen, Weizhu , year =. 2305.11738 , archivePrefix=

    arXiv

  13. [21]

    and Wettig, Alexander and Lieret, Kilian and Yao, Shunyu and Narasimhan, Karthik and Press, Ofir , booktitle =

    Yang, John and Jimenez, Carlos E. and Wettig, Alexander and Lieret, Kilian and Yao, Shunyu and Narasimhan, Karthik and Press, Ofir , booktitle =. 2024 , url =

    2024

  14. [22]

    and Tang, Xiangru and Zhuge, Mingchen and Pan, Jiayi and Song, Yueqi and Li, Bowen and Singh, Jaskirat and Tran, Hoang H

    Wang, Xingyao and Li, Boxuan and Song, Yufan and Xu, Frank F. and Tang, Xiangru and Zhuge, Mingchen and Pan, Jiayi and Song, Yueqi and Li, Bowen and Singh, Jaskirat and Tran, Hoang H. and Li, Fuqiang and Ma, Ren and Zheng, Mingzhang and Qian, Bill and Shao, Yanjun and Muennigh...

    2025

  15. [23]

    Gauthier, Paul , year =

  16. [24]

    2025 , howpublished =

    Claude Code:. 2025 , howpublished =

    2025

  17. [25]

    2025--2026 , howpublished =

    2025

  18. [26]

    2024 , howpublished =

    Introducing. 2024 , howpublished =

    2024

  19. [27]

    2026 , howpublished =

    Cursor: An AI Code Editor and Agentic Coding Environment , author =. 2026 , howpublished =

    2026

  20. [28]

    2026 , howpublished =

    Hermes Agent: Open-Source AI Agent with Persistent Memory , author =. 2026 , howpublished =

    2026

  21. [29]

    2026 , howpublished =

    2026

  22. [30]

    2605.27922 , archivePrefix=

    Yao, Yilun and Tan, Xinyu and Liu, Chao-Hsuan and Li, Yaoming and Wang, Zhengyang and Yu, Wenhan and Tan, Zhewen and Tian, Yuxuan and Zhao, Guangxiang and Sun, Lin and Zhang, Xiangzheng and Yang, Tong , year =. 2605.27922 , archivePrefix=

    arXiv

  23. [31]

    2026 , eprint =

    The Scaffold Effect in Coding Agents: Harness Choice as a Hidden Variable in Coding-Agent Evaluation , author =. 2026 , eprint =

    2026

  24. [32]

    and Yang, John and Wettig, Alexander and Yao, Shunyu and Pei, Kexin and Press, Ofir and Narasimhan, Karthik , booktitle =

    Jimenez, Carlos E. and Yang, John and Wettig, Alexander and Yao, Shunyu and Pei, Kexin and Press, Ofir and Narasimhan, Karthik , booktitle =. 2024 , url =

    2024

  25. [33]

    and Shaw, Alexander G

    Merrill, Mike A. and Shaw, Alexander G. and Carlini, Nicholas and others , booktitle =. 2026 , eprint =

    2026

  26. [34]

    2026 , howpublished =

    Why. 2026 , howpublished =

    2026

  27. [35]

    Deng, Xiang and Da, Jeff and Pan, Edwin and He, Yannis Yiming and Ide, Charles and Garg, Kanak and Lauffer, Niklas and Park, Andrew and Pasari, Nitin and Rane, Chetan and Sampath, Karmini and Krishnan, Maya and Kundurthy, Srivatsa and Hendryx, Sean and Wang, Zifan and Bharadwa...

  28. [36]

    2404.07972 , archivePrefix=

    Xie, Tianbao and Zhang, Danyang and Chen, Jixuan and Li, Xiaochuan and Zhao, Siheng and Cao, Ruisheng and Hua, Toh Jing and Cheng, Zhoujun and Shin, Dongchan and Lei, Fangyu and Liu, Yitao and Xu, Yiheng and Zhou, Shuyan and Savarese, Silvio and Xiong, Caiming and Zhong, Victo...

    arXiv

  29. [37]

    2605.03546 , archivePrefix=

    Yang, John and Lieret, Kilian and Ma, Jeffrey and Thakkar, Parth and Pedchenko, Dmitrii and Sootla, Sten and McMilin, Emily and Yin, Pengcheng and Hou, Rui and Synnaeve, Gabriel and Yang, Diyi and Press, Ofir , year =. 2605.03546 , archivePrefix=

    arXiv

  30. [38]

    2605.10912 , archivePrefix=

    Ding, Shuangrui and Dai, Xuanlang and Xing, Long and Ding, Shengyuan and Liu, Ziyu and Yang, Jingyi and Yang, Penghui and Zhang, Zhixiong and Wei, Xilin and Fang, Xinyu and Ma, Yubo and Duan, Haodong and Shao, Jing and Wang, Jiaqi and Lin, Dahua and Chen, Kai and Zang, Yuhang ...

    arXiv

  31. [39]

    2026 , eprint =

    Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments , author =. 2026 , eprint =

    2026

  32. [40]

    Do Androids Dream of Breaking the Game? Systematically Auditing

    Wang, Hao and Li, Hanchen and Mang, Qiuyang and Cheung, Alvin and Sen, Koushik and Song, Dawn , year =. Do Androids Dream of Breaking the Game? Systematically Auditing. 2605.12673 , archivePrefix=

    arXiv

  33. [41]

    Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic

    Shao, Jiaqi and Chen, Hanck and Zhang, Wei and Pan, Maxm and Luo, Bing , year =. Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic. 2607.22368 , archivePrefix=

    arXiv

  34. [42]

    2025 , note =

    Wijk, Hjalmar and Lin, Tao and Becker, Joel and Jawhar, Sami and Parikh, Neev and Broadley, Thomas and Chan, Lawrence and Chen, Michael and Clymer, Joshua and Dhyani, Jai and Ericheva, Elena and Garcia, Katja and Goodrich, Brian and Jurkovic, Nikola and Kinniment, Megan and La...

    2025

  35. [43]

    Measuring

    Kwa, Thomas and West, Ben and Becker, Joel and others , journal =. Measuring

  36. [44]

    2024 , note =

    Liu, Xiao and Yu, Hao and Zhang, Hanchen and Xu, Yifan and Lei, Xuanyu and Lai, Hanyu and Gu, Yu and Ding, Hangliang and Men, Kaiwen and Yang, Kejuan and Zhang, Shudan and Deng, Xiang and Zeng, Aohan and Du, Zhengxiao and Zhang, Chenhui and Shen, Sheng and Zhang, Tianjun and S...

    2024

  37. [45]

    2025 , note =

    Jain, Naman and Han, King and Gu, Alex and Li, Wen-Ding and Yan, Fanjia and Zhang, Tianjun and Wang, Sida and Solar-Lezama, Armando and Sen, Koushik and Stoica, Ion , booktitle =. 2025 , note =

    2025

  38. [46]

    Yu, Hongli and Chen, Tinghong and Feng, Jiangtao and Chen, Jiangjie and Dai, Weinan and Yu, Qiying and Zhang, Ya-Qin and Ma, Wei-Ying and Liu, Jingjing and Wang, Mingxuan and Zhou, Hao , journal =

  39. [47]

    and Macarini, Luiz A

    Borro, Luiz C. and Macarini, Luiz A. B. and Tindall, Gordon and Montero, Michael and Struck, Adam B. , year =. Memori: A Persistent Memory Layer for Efficient, Context-Aware. 2603.19935 , archivePrefix=

  40. [48]

    Springdrift: An Auditable Persistent Runtime for

    Brady, Seamus , year =. Springdrift: An Auditable Persistent Runtime for. 2604.04660 , archivePrefix=

    arXiv

  41. [49]

    Anonymous

    Durieux, Thomas , year =. Anonymous

  42. [50]

    2023 , eprint =

    Mialon, Gr. 2023 , eprint =

    2023

  43. [51]

    2410.07095 , archivePrefix=

    Chan, Jun Shern and Chowdhury, Neil and Jaffe, Oliver and Aung, James and Sherburn, Dane and Mays, Evan and Starace, Giulio and Liu, Kevin and Maksin, Leon and Patwardhan, Tejal and Madry, Aleksander and Weng, Lilian , year =. 2410.07095 , archivePrefix=

    arXiv

  44. [52]

    Aho and Jeffrey D

    Alfred V. Aho and Jeffrey D. Ullman , title =. 1972

    1972

  45. [53]

    Dan Gusfield , title =. 1997

    1997

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.