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Paper Citation Record · LEDGER

Recursive Synthesis for Long-Horizon Terminal Tasks

As of 9 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 0 inbound Pith citation observations for arXiv:2608.05466.

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

pith.paper-citation-record.v1
2608.05466 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:35:01.615574Z

measured 65 of 65 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

65 of 65 outbound references displayed

  • verified exact1
  • verified fuzzy8
  • unresolved55
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4751f222-a25a-4775-b46b-4ee03e3588fc · outbound

This paper cites Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.

Recursive Synthesis for Long-Horizon Terminal Tasks Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Reference 1

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source=pdf_text observed=2026-08-08T12:35:01.302551Z digest=sha256:16f07b72ac2768bd71ecf4d891d0b62f35f73cce141a901e005c12df3495d5b6

Observation a15515dc-8c1d-4801-8211-13d99d0058d8 · outbound

This paper cites From language to action: a review of large language models as autonomous agents and tool users.Artificial Intelligence Review, 59(2):71, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks From language to action: a review of large language models as autonomous agents and tool users.Artificial Intelligence Review, 59(2):71, 2026

Reference 2

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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=pdf_text observed=2026-08-08T12:35:01.308995Z digest=sha256:ecfb164f91d5dc52841028a5affb1279054617b520cff653f2b90ef959c3bed8

Observation 1f10b2bb-9552-4332-8ac2-e153443340b3 · outbound

This paper cites TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks.

Recursive Synthesis for Long-Horizon Terminal Tasks TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks

Reference 3

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source=pdf_text observed=2026-08-08T12:35:01.313844Z digest=sha256:b57e80f55496ea42f74df75b948783ddbf85242ef54331210058f7251979137d

Observation 69728056-387a-4e4b-ac2a-689ae3c85b8b · outbound

This paper cites Deepseek-v4: Towards highly efficient million-token context intelligence, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks Deepseek-v4: Towards highly efficient million-token context intelligence, 2026

Reference 4

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source=pdf_text observed=2026-08-08T12:35:01.319160Z digest=sha256:1c824369e908f161d6ce2231a72a257aefcca509ce0c9902ebcecc72912b1de7

Observation 329d895a-373f-43b2-bc37-e951ac911eee · outbound

This paper cites SWE-Marathon: Can Agents Autonomously Complete Ultra-Long-Horizon Software Work?.

Recursive Synthesis for Long-Horizon Terminal Tasks SWE-Marathon: Can Agents Autonomously Complete Ultra-Long-Horizon Software Work?

Reference 5

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source=pdf_text observed=2026-08-08T12:35:01.324108Z digest=sha256:464623bf26c1c51880f58f40facfdcff7fb14fe6dcaa589da439e1d5d337a2b1

Observation cca10a6e-b833-4eab-afb1-e89759fd8640 · outbound

This paper cites A survey on the optimization of large language model-based agents.ACM Computing Surveys, 58(9):1–37, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks A survey on the optimization of large language model-based agents.ACM Computing Surveys, 58(9):1–37, 2026

Reference 6

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raw_fallback, observed 2026-08-08T12:35:03.448752Z

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=2026-08-08T12:35:01.334134Z digest=sha256:693345f9fcc0c272ce274e0d1e6e29cec08b03c5d92b587f519779bead38ffd5

Observation 884f2c83-9d4e-42a0-88c4-4096f87d5cca · outbound

This paper cites Webevolver: Enhancing web agent self-improvement with coevolving world model, 2025.

Recursive Synthesis for Long-Horizon Terminal Tasks Webevolver: Enhancing web agent self-improvement with coevolving world model, 2025

Reference 7

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source=pdf_text observed=2026-08-08T12:35:01.338853Z digest=sha256:c9dd384a2d28adb5e72b20e1f081b9e094a2ee313bb89ead848abf42113181a0

Observation f9a59c73-280f-4920-b034-b8f13c837c20 · outbound

This paper cites Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training.

Recursive Synthesis for Long-Horizon Terminal Tasks Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training

Reference 8

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:35:01.344029Z digest=sha256:45f9c619d503ed6e3280246cb75065cf3cd727ca18821d2109dc8b0bff82dd68

Observation d14b23df-9113-4bde-b778-ec6e21c9a1a5 · outbound

This paper cites Goodman, and Dimitris Papailiopoulos.

Recursive Synthesis for Long-Horizon Terminal Tasks Goodman, and Dimitris Papailiopoulos

Reference 9

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source=pdf_text observed=2026-08-08T12:35:01.348930Z digest=sha256:17f2dfc6c5789eb0b6169eac496a8e7643ab6511a14eb6919f8f77892f80c327

Observation 1955cd5c-6f20-423d-b1c3-8a0ef0f599f9 · outbound

This paper cites Fung, Kun Wang, Linfeng Zhang, and Jing Shao.

Recursive Synthesis for Long-Horizon Terminal Tasks Fung, Kun Wang, Linfeng Zhang, and Jing Shao

Reference 10

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source=pdf_text observed=2026-08-08T12:35:01.353745Z digest=sha256:8e52c5e41c2f327ec8b2e71458d9405ee243f70274ac60ae46f22d9200b15846

Observation 8d8e5b0c-886c-478a-893e-65510f9a7e02 · outbound

This paper cites Harbor: A framework for evaluating and optimizing agents and models in container environments, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks Harbor: A framework for evaluating and optimizing agents and models in container environments, 2026

Reference 11

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source=pdf_text observed=2026-08-08T12:35:01.358317Z digest=sha256:8b9519d2517375e068f2c479a6483fe2bd99d45a2d4e4e743c0724524c99d6aa

Observation 9db325c0-eb7f-493b-9c51-cc4702847e13 · outbound

This paper cites Visplay: Self-evolving vision- language models from images.arXiv preprint arXiv:2511.15661, 2025.

Recursive Synthesis for Long-Horizon Terminal Tasks Visplay: Self-evolving vision- language models from images.arXiv preprint arXiv:2511.15661, 2025

Reference 12

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source=pdf_text observed=2026-08-08T12:35:01.363192Z digest=sha256:6748183c7d2cd0f6dd93a775e09b17f2d35840c0dae84eb9cfed404f3fcdb3bf

Observation 4aec1f12-e28b-4ee8-bbee-b2ee62967581 · outbound

This paper cites V-STaR: Training Verifiers for Self-Taught Reasoners.

Recursive Synthesis for Long-Horizon Terminal Tasks V-STaR: Training Verifiers for Self-Taught Reasoners

Reference 13

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source=pdf_text observed=2026-08-08T12:35:01.368031Z digest=sha256:b2e64b3c42b1f23a4abb42541284ea2c03644a5533ed97865b159f460bf61022

Observation f74f5342-4b66-46b2-b99f-d67ac79e12a3 · outbound

This paper cites CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents.

Recursive Synthesis for Long-Horizon Terminal Tasks CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents

Reference 14

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source=pdf_text observed=2026-08-08T12:35:01.373257Z digest=sha256:4205e21cdfd1bdd568e88792f8b9f7774a9b4a9144c146371e3db9ed719c29a7

Observation af4ea242-212d-44d3-9029-a59d4d8b53e5 · outbound

This paper cites R-Zero: Self-Evolving Reasoning LLM from Zero Data.

Recursive Synthesis for Long-Horizon Terminal Tasks R-Zero: Self-Evolving Reasoning LLM from Zero Data

Reference 15

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source=pdf_text observed=2026-08-08T12:35:01.378303Z digest=sha256:713a6c9fafb36a73b86cb61ee7f2a85157c4748d1d2105d6c657ca148f2847be

Observation aa3a79ee-4f6f-4370-a4d9-5e8d187c5a6b · outbound

This paper cites Tmax: A simple recipe for terminal agents.

Recursive Synthesis for Long-Horizon Terminal Tasks Tmax: A simple recipe for terminal agents

Reference 16

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source=pdf_text observed=2026-08-08T12:35:01.383123Z digest=sha256:c05198de8fa084df6e626ffab040cc6e83957dbf8ae4fe8b5ba0a1855235c9f7

Observation 23b7dc0e-0a83-43ea-bd7f-8a97e0d40442 · outbound

This paper cites Swe-bench: Can language models resolve real-world github issues? In B.

Recursive Synthesis for Long-Horizon Terminal Tasks Swe-bench: Can language models resolve real-world github issues? In B

Reference 17

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raw_fallback, observed 2026-08-08T12:35:03.409195Z

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=2026-08-08T12:35:01.388157Z digest=sha256:0792389194e18840da2d4a17ac588a92efab3b28e7a999bd5042cc284cbfa2c4

Observation fdbb748b-6bad-4e35-833c-65bb425646de · outbound

This paper cites Measuring AI Ability to Complete Long Software Tasks.

Recursive Synthesis for Long-Horizon Terminal Tasks Measuring AI Ability to Complete Long Software Tasks

Reference 18

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source=pdf_text observed=2026-08-08T12:35:01.393285Z digest=sha256:b7705242468477970340d806c1162a60bb05248f51aaa2ce098f27ce27fb1628

Observation 070ea0a5-1f76-4730-a143-e1040b2e3955 · outbound

This paper cites Self-Rewarding Vision-Language Model via Reasoning Decomposition.

Recursive Synthesis for Long-Horizon Terminal Tasks Self-Rewarding Vision-Language Model via Reasoning Decomposition

Reference 19

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source=pdf_text observed=2026-08-08T12:35:01.398285Z digest=sha256:06176c6b44e366ab63b2a82cc2c0ebbd31c144d9922a5985df253e32d5482100

Observation b1a70485-2250-434e-9bf7-99f0fa4a63ad · outbound

This paper cites Mm-zero: Self-evolving multi-model vision language models from zero data.

Recursive Synthesis for Long-Horizon Terminal Tasks Mm-zero: Self-evolving multi-model vision language models from zero data

Reference 20

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source=pdf_text observed=2026-08-08T12:35:01.403381Z digest=sha256:2516fa202f2a1c5697bc09b88408743134bb04a4407700b8e0fe59ac361157c4

Observation f1b89008-24a9-40b4-bcdf-70106faf04c8 · outbound

This paper cites Long-Horizon-Terminal-Bench: Testing the Limits of Agents on Long-Horizon Terminal Tasks with Dense Reward-Based Grading.

Recursive Synthesis for Long-Horizon Terminal Tasks Long-Horizon-Terminal-Bench: Testing the Limits of Agents on Long-Horizon Terminal Tasks with Dense Reward-Based Grading

Reference 21

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source=pdf_text observed=2026-08-08T12:35:01.407591Z digest=sha256:8a11c05fdb2223e9548e6a8e1ab8a17b0c95aded0a52b3233d11a116cf2fd37d

Observation 93372bca-a708-461a-baa1-fee350f67689 · outbound

This paper cites Agentbench: Evaluating llms as agents,.

Recursive Synthesis for Long-Horizon Terminal Tasks Agentbench: Evaluating llms as agents,

Reference 22

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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=pdf_text observed=2026-08-08T12:35:01.412016Z digest=sha256:99d4f69e565a869a2d92240f2227100034bb1271ed7ab18554b920e8bf0a0c2e

Observation e3dca9b8-f0a3-480e-b867-c2049c20edd0 · outbound

This paper cites Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces.

Recursive Synthesis for Long-Horizon Terminal Tasks Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Reference 23

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source=pdf_text observed=2026-08-08T12:35:01.420886Z digest=sha256:20daf4a2e00c671acce8957bb41f65dba115182a37a1c58c52d0d7253ebef260

Observation 3a062bd9-f771-4714-abd8-d610024726b7 · outbound

This paper cites GAIA: a benchmark for General AI Assistants.

Recursive Synthesis for Long-Horizon Terminal Tasks GAIA: a benchmark for General AI Assistants

Reference 24

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source=pdf_text observed=2026-08-08T12:35:01.425569Z digest=sha256:b05a06cfdfe11c86214e17e8aec85d22f8c4be02db6ac13c68a7bad24d6710ff

Observation 81f022bb-9ae9-45ea-860f-4044c6fe7478 · outbound

This paper cites Training Software Engineering Agents and Verifiers with SWE-Gym.

Recursive Synthesis for Long-Horizon Terminal Tasks Training Software Engineering Agents and Verifiers with SWE-Gym

Reference 25

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source=pdf_text observed=2026-08-08T12:35:01.430355Z digest=sha256:13a0d3085bc9c929cfabadc66a224eac5b4b82b1724a1ed51454d92d48795565

Observation 9bcd7778-c3ac-4d83-8b5f-e5b63395d5ea · outbound

This paper cites LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents.

Recursive Synthesis for Long-Horizon Terminal Tasks LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents

Reference 26

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local_arxiv, observed 2026-08-08T12:35:02.595199Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T12:35:01.435238Z digest=sha256:93be107120728efc70693e3ce6614dad9548e5047dcd0b7d1b4220130300f1e8

Observation 26531a17-9801-4f31-95a4-df28cdd8236a · outbound

This paper cites On data engineering for scaling llm terminal capabilities, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks On data engineering for scaling llm terminal capabilities, 2026

Reference 27

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source=pdf_text observed=2026-08-08T12:35:01.440348Z digest=sha256:781410b7dc561bc8c13116df117f2296e9070c4fc547ba9f0b0c3be15e920a6a

Observation 818058ae-800e-4e9e-b1d8-8a1fc22eb194 · outbound

This paper cites Self-Consistency Preference Optimization.

Recursive Synthesis for Long-Horizon Terminal Tasks Self-Consistency Preference Optimization

Reference 28

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source=pdf_text observed=2026-08-08T12:35:01.444948Z digest=sha256:38a6f62805a68a878d3f2127f5919d2f2cca97c45667a24520b2a145de194c4c

Observation f7e921a1-b99a-40a7-9c36-ba29a007f1c0 · outbound

This paper cites OpenThoughts-Agent: Data Recipes for Agentic Models.

Recursive Synthesis for Long-Horizon Terminal Tasks OpenThoughts-Agent: Data Recipes for Agentic Models

Reference 29

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metadata mismatch
local_arxiv, observed 2026-08-08T12:35:02.471780Z

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=2026-08-08T12:35:01.449971Z digest=sha256:5727e51653fba689be02043d37c0377a14c8b0ea2fbb33f058757a1c48138134

Observation 7b06f98d-147b-4eea-9a8e-a5f2c6131680 · outbound

This paper cites SETA: Scaling Environments for Terminal Agents.

Recursive Synthesis for Long-Horizon Terminal Tasks SETA: Scaling Environments for Terminal Agents

Reference 30

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source=pdf_text observed=2026-08-08T12:35:01.454584Z digest=sha256:2ff3261bd20f103aa1451e18450a207db1ee8816423672d25f3d9a00ab684b8c

Observation c2689870-d8ac-4522-a585-d2f1e16e5a9b · outbound

This paper cites Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models.

Recursive Synthesis for Long-Horizon Terminal Tasks Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Reference 31

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source=pdf_text observed=2026-08-08T12:35:01.459919Z digest=sha256:d8d8d2d02ce74cd363f2dbc0882165915c70f38afe211053f96fbac5481d811d

Observation dd7ade03-c98e-42fe-b544-e3b639fd4214 · outbound

This paper cites EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis.

Recursive Synthesis for Long-Horizon Terminal Tasks EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis

Reference 32

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source=pdf_text observed=2026-08-08T12:35:01.465550Z digest=sha256:48492447e7899d28e2b2780904706a2b42134d77e6d2c8fbb548970777fa3c56

Observation 391e5d70-936a-475f-8192-a738308d438b · outbound

This paper cites Scaleenv: Scaling environment synthesis from scratch for generalist interactive tool-use agent training, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks Scaleenv: Scaling environment synthesis from scratch for generalist interactive tool-use agent training, 2026

Reference 33

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source=pdf_text observed=2026-08-08T12:35:01.471490Z digest=sha256:bb39571ad37ea6f14d81917ae3849aef6aceee4e5b9bc91b710cece99325f653

Observation f75fe1db-c6c7-42d2-b504-d3ab03f32073 · outbound

This paper cites Apex-agents, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks Apex-agents, 2026

Reference 34

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source=pdf_text observed=2026-08-08T12:35:01.475984Z digest=sha256:3e2c1c85ed8bafc97ae61c992f61f6086c3151922437f3e138afce811aead9f1

Observation 59ac1581-8dd3-4cbe-bbdb-b6f08ad8e71c · outbound

This paper cites Swe-bench++: A framework for the scalable generation of software engineering benchmarks from open-source repositories, 2025.

Recursive Synthesis for Long-Horizon Terminal Tasks Swe-bench++: A framework for the scalable generation of software engineering benchmarks from open-source repositories, 2025

Reference 35

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source=pdf_text observed=2026-08-08T12:35:01.481690Z digest=sha256:d6733c836f6831841b2eb0f4f592f92ac6f38e9ef3897c94738a0f10ceb1eca8

Observation b73eb0ae-1e24-46a0-acdd-9a924a810255 · outbound

This paper cites OpenHands: An Open Platform for AI Software Developers as Generalist Agents.

Recursive Synthesis for Long-Horizon Terminal Tasks OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Reference 36

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source=pdf_text observed=2026-08-08T12:35:01.486636Z digest=sha256:89257b114b097021d0920f3c0bbc7e6516e0f20dd43562de1fd783bf69f28245

Observation e3d7f8c9-ef03-4028-bcd5-ea8e4b3244fb · outbound

This paper cites Llms as scalable, general-purpose simulators for evolving digital agent training,.

Recursive Synthesis for Long-Horizon Terminal Tasks Llms as scalable, general-purpose simulators for evolving digital agent training,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.491438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.491438Z digest=sha256:009dee786dd9cfca08f4e5cbf1ef94e1a4f1684ed91b93c69f97d1a300e46acc

Observation 762ab5bd-7461-4c05-bec4-bd2578a0d662 · outbound

This paper cites BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution.

Recursive Synthesis for Long-Horizon Terminal Tasks BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.501875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.501875Z digest=sha256:2f57a866e3ec998f4cda37be7004cf26715a05308249e37386f358f7c31c2143

Observation 6e201482-5bee-4e4a-9bb7-a9d12a250cc1 · outbound

This paper cites Autowebworld: Synthesizing infinite verifiable web environments via finite state machines, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks Autowebworld: Synthesizing infinite verifiable web environments via finite state machines, 2026

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.506696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.506696Z digest=sha256:20eb5fd9c3d96058e3ed1eeefbd0a01500afe2eac75eca0851d18d1f4b60330f

Observation f0ec4313-9275-4087-a681-702e7034aa58 · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.496200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.496200Z digest=sha256:81b61c61b9e152f69a469040c8029d3b2a79601d8969b83ec6769be288d07637

Observation abd49d4b-6f43-44d2-8f0d-ffa3be579ecc · outbound

This paper cites OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments.

Recursive Synthesis for Long-Horizon Terminal Tasks OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.516490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.516490Z digest=sha256:f7a5de50c9e51e77cd7d842d9f55200d354c9778c064d3899fffd6f828e6b8b9

Observation 38d9527c-56c1-4ec5-8657-19b07ab3dfeb · outbound

This paper cites Wizardlm: Empowering large pre-trained language models to follow complex instructions.

Recursive Synthesis for Long-Horizon Terminal Tasks Wizardlm: Empowering large pre-trained language models to follow complex instructions

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:35:03.369349Z

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=2026-08-08T12:35:01.521513Z digest=sha256:fff3b8d5105c8667af1e9f1ef5c3a0e6416cdd2a2a0861f4fe44f043fc5f7568

Observation 729330c6-6025-42dc-83e1-522d60a49f1b · outbound

This paper cites Agent0: Unleashing self-evolving agents from zero data via tool-integrated reasoning, 2025.

Recursive Synthesis for Long-Horizon Terminal Tasks Agent0: Unleashing self-evolving agents from zero data via tool-integrated reasoning, 2025

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.511524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.511524Z digest=sha256:a20e3c01b9ecf1d62c03c3e15778320aae200ff757c1c371203a9e9db4c32134

Observation 9109421e-0c42-406c-98eb-dd6d0bba6352 · outbound

This paper cites Self-Rewarding Language Models.

Recursive Synthesis for Long-Horizon Terminal Tasks Self-Rewarding Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.531330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.531330Z digest=sha256:b1aac84463609904cd149dfd47626900a33b29cfe5ca6789902e0a60e407e87f

Observation cc1409e5-004c-4d77-988e-33d9195d8939 · outbound

This paper cites Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving.

Recursive Synthesis for Long-Horizon Terminal Tasks Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.535689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.535689Z digest=sha256:939649817b79dda247a8e8ed908b96ee65d623a1190dd0e70d1e2e18edac2411

Observation 4aaa81d3-0dd6-42cd-820f-18f95f0264c9 · outbound

This paper cites SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering.

Recursive Synthesis for Long-Horizon Terminal Tasks SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.526085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.526085Z digest=sha256:0b5926646159e781b1d6bb5b4bb74a1bf8b1da292e153d491186cf33ebb4dba9

Observation 086199cf-c30f-4789-adfc-39e11916fa3d · outbound

This paper cites RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments.

Recursive Synthesis for Long-Horizon Terminal Tasks RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.545456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.545456Z digest=sha256:04ce1fa71935dcdca1277ba52a16853ce756c2f2980b54d1c0fd71409b9ec650

Observation fa4a0800-592c-458a-bb7d-a8380d0c1fbd · outbound

This paper cites InfiniteWeb: Scalable Web Environment Synthesis for GUI Agent Training.

Recursive Synthesis for Long-Horizon Terminal Tasks InfiniteWeb: Scalable Web Environment Synthesis for GUI Agent Training

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.549784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.549784Z digest=sha256:01416728c28c87c8fa26797b47e258947ae333f8d336a69289de8432e3c2f94b

Observation b1944726-6aad-4fc8-b534-cb506d1cd2e2 · outbound

This paper cites Star: Bootstrapping reasoning with reasoning.

Recursive Synthesis for Long-Horizon Terminal Tasks Star: Bootstrapping reasoning with reasoning

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.540492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.540492Z digest=sha256:94267414ebc10bb0e73ec1bd12341f4a86c957749cf0002576661e5bb00e122c

Observation 8698f68a-6fc2-4622-a271-3aa74f7735bf · outbound

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

Recursive Synthesis for Long-Horizon Terminal Tasks WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.558740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.558740Z digest=sha256:32d98c1dd3c147945fff34344c342f85f6c30a21ef159f31d4bdef780c275b6f

Observation 2e90da6b-1b81-43de-bc45-cbe34f63e5c0 · outbound

This paper cites Self-challenging lan- guage model agents.

Recursive Synthesis for Long-Horizon Terminal Tasks Self-challenging lan- guage model agents

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:35:03.344626Z

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=2026-08-08T12:35:01.563424Z digest=sha256:a121c203432e239b499e706d8a1f8bce60d8c95feeae917870cad39ed7b4c8fe

Observation 2e6ed6e5-ba9a-4b21-a66f-3db5c4a8ae99 · outbound

This paper cites Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

Recursive Synthesis for Long-Horizon Terminal Tasks Absolute Zero: Reinforced Self-play Reasoning with Zero Data

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.553746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.553746Z digest=sha256:66a86759857eecb9bebaf855f2290882592a362d6d09fd4eb0a64b3de149ee77

Observation b7ff8250-9818-4272-839f-3f0875a1336f · outbound

This paper cites fix this bug.

Recursive Synthesis for Long-Horizon Terminal Tasks fix this bug

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.572361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.572361Z digest=sha256:248257633be57e4a223c95530d432decf116fc1c2e69b374800f0431489b1607

Observation eac52f9b-f66f-41ea-ad23-52aecb70d653 · outbound

This paper cites Termigen: High-fidelity environment and robust trajectory synthesis for terminal agents, 2026.

Recursive Synthesis for Long-Horizon Terminal Tasks Termigen: High-fidelity environment and robust trajectory synthesis for terminal agents, 2026

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.568019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.568019Z digest=sha256:e372711d53b546c8761c1b253f87ad6211b37fa227a2a157d99424466d75b9c0

Observation 65d712c6-8fd3-43e3-9b10-218b501f55c8 · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.330156Z

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=2026-08-08T12:35:01.578764Z digest=sha256:81b5cdaafa0e3b5a827f017f618233451f7441d532b2345762a24ef355e3ea91

Observation 7945c93a-e1b9-4e3d-8d89-b39a7815200f · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.315673Z

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=2026-08-08T12:35:01.583427Z digest=sha256:471dfc2a47f161295cffa8e07b5c817162349bb6ced6396553ee1b65d56889a6

Observation 5e41e0c0-5d1b-4bbf-ac40-64942545073d · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.300959Z

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=2026-08-08T12:35:01.587964Z digest=sha256:e2b7b5063c95aff6806dd1c5c58921748bd999588d8957e68693a09ac3284961

Observation be9f50aa-88a0-45d5-8f78-c13f1fcab05d · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.284962Z

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=2026-08-08T12:35:01.592376Z digest=sha256:5374d2e2f763e59db0ba968f0f45c271d4983970ff57390e61abf2a12174131b

Observation fdd1eb42-3b5a-4b8b-9bc2-755602fabd3b · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.268785Z

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=2026-08-08T12:35:01.597325Z digest=sha256:c9ddd48018e3b8214d92ba353f2c7e4628baddb203bdf668221711977f7a74b5

Observation e6b5e406-e6e5-43f9-909a-3c9612176c37 · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.254594Z

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=2026-08-08T12:35:01.601936Z digest=sha256:ea07dbfcc1e3f0c5634299eb002fe04efd806131e5506844af9a4cb2c92a264e

Observation 3440699a-1c81-49ba-8a15-b7d892117e93 · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 63

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.239621Z

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=2026-08-08T12:35:01.606600Z digest=sha256:4fad147dcc7726fd269a80dd25f53d12e60894d7ee84b9f16bfc074dd21d23af

Observation eb565eab-b642-413e-9647-dbc85a94026c · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 64

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.224772Z

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=2026-08-08T12:35:01.611257Z digest=sha256:8e82d3ea94a1206acdb61362e64c56c230df8d5611d7bd7fda555d5f1f6e4ef6

Observation 499ebf7c-6274-4ee3-bd1a-68d3c740cef9 · outbound

This paper cites until tests pass.

Recursive Synthesis for Long-Horizon Terminal Tasks until tests pass

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T12:35:03.210164Z

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=2026-08-08T12:35:01.615574Z digest=sha256:2ff3b536db563301dc443c37e1d2c1f2d3390add3e57f2f36f75e5a8ce3892b7

Observation 83c979f1-9a6d-4b75-85fc-9a87086c735c · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

Recursive Synthesis for Long-Horizon Terminal Tasks AgentBench: Evaluating LLMs as Agents

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-08T12:35:01.416279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:35:01.416279Z digest=sha256:286e250413b85685d62fcd77abf76481928e8fcc72ddb7d26f62cc9eb0468755

Observation 3804f896-5336-4003-9f00-41dcb5ef1009 · outbound

This paper cites an unresolved cited work.

Recursive Synthesis for Long-Horizon Terminal Tasks Unresolved cited work

Reference 2026

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:35:03.463141Z

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=2026-08-08T12:35:01.329215Z digest=sha256:04066c033761a23f1ef3403864a91ca074a6c666c4dfcdcc713bd339140b26a0

Pith citing papers

No inbound Pith citation observations are available.