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Paper Citation Record · LEDGER

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents

As of 22 August 2026, this Paper Citation Record lists 100 of 130 outbound references and 0 inbound Pith citation observations for arXiv:2607.18859.

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

pith.paper-citation-record.v1
2607.18859 v1

Coverage vector

measured 100 of 130 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:12:01.010734Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

100 of 130 outbound references displayed

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  • verified fuzzy0
  • unresolved100
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation c6fa0a1b-0c79-4561-b9fa-5dee1fdb54f4 · outbound

This paper cites Autocoderover: Autonomous program improvement,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Autocoderover: Autonomous program improvement,

Reference 1

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source=pdf_text observed=2026-08-01T14:11:53.175151Z digest=sha256:d6b306216a9580d6ca457d3af1034fc6a0c5f7b10356a4f9deeb27d668f58773

Observation a4093ce2-58fd-4a5c-8414-cd5970387e96 · outbound

This paper cites DeepSeek-V3 Technical Report.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents DeepSeek-V3 Technical Report

Reference 2

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Observation 0e72eb4a-0ef9-4894-bbed-87a4249ed249 · outbound

This paper cites GPT-4 Technical Report.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents GPT-4 Technical Report

Reference 3

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Observation b898073b-b22e-4d48-ae8b-a95c0f7b4bd8 · outbound

This paper cites Qwen3 Technical Report.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Qwen3 Technical Report

Reference 4

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Observation 9dd343e5-fc9d-4860-8b16-0978c81ddc94 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 5

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Observation ea1937cf-e119-4de3-9f08-b543dda65a5c · outbound

This paper cites Swe-agent: Agent-computer interfaces enable automated software engineering,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Swe-agent: Agent-computer interfaces enable automated software engineering,

Reference 6

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Observation 206de61d-659f-416d-813f-b7d142a34fbd · outbound

This paper cites Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling

Reference 7

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Observation 83d4b821-b46f-45c3-a75f-63ba2fb142cc · outbound

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

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Reference 8

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Observation 09d0bb56-bbc1-4911-b680-a4645e29280d · outbound

This paper cites Large Language Model-Based Agents for Software Engineering: A Survey.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Large Language Model-Based Agents for Software Engineering: A Survey

Reference 9

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Observation e3fc6589-1c39-4e22-a89d-331c82b9f4c4 · outbound

This paper cites A deep relevance matching model for ad-hoc retrieval,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents A deep relevance matching model for ad-hoc retrieval,

Reference 10

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Observation 2ce01665-0a88-4705-8408-8ed32ae7acb1 · outbound

This paper cites CodeMonkeys: Scaling Test-Time Compute for Software Engineering.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents CodeMonkeys: Scaling Test-Time Compute for Software Engineering

Reference 11

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Observation dbf3880c-b063-4ff5-b9a5-9b4d8b35a5bd · outbound

This paper cites On the limits of language generation: Trade-offs between hallucination and mode-collapse,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents On the limits of language generation: Trade-offs between hallucination and mode-collapse,

Reference 12

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Observation 35764025-8848-48fa-a297-59328b356b97 · outbound

This paper cites The curious decline of linguistic diversity: Training language models on synthetic text,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents The curious decline of linguistic diversity: Training language models on synthetic text,

Reference 13

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Observation 6074aa56-d4d9-40ca-b93f-617c9d3e0a42 · outbound

This paper cites One fish, two fish, but not the whole sea: Alignment reduces language models’ conceptual diversity,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents One fish, two fish, but not the whole sea: Alignment reduces language models’ conceptual diversity,

Reference 14

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Observation 7e9964b5-2d15-4794-ac5a-55b526103f2e · outbound

This paper cites Se-agent: Self-evolution trajectory optimiza- tion in multi-step reasoning with llm-based agents,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Se-agent: Self-evolution trajectory optimiza- tion in multi-step reasoning with llm-based agents,

Reference 15

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Observation a7690275-b940-41e3-b0bb-54bff2727fc5 · outbound

This paper cites Agentless: Demystifying LLM-based Software Engineering Agents.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Agentless: Demystifying LLM-based Software Engineering Agents

Reference 16

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Observation 3f4a65d6-806c-4dd3-8323-225e858af8c6 · outbound

This paper cites Locagent: Graph-guided llm agents for code localization,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Locagent: Graph-guided llm agents for code localization,

Reference 17

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Observation 25d091ef-2005-4937-8504-5faaea407f65 · outbound

This paper cites Introducing SWE-bench Verified,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Introducing SWE-bench Verified,

Reference 18

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Observation 1b2698a8-ccf7-4937-baf6-80ce7eb94e3f · outbound

This paper cites SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement

Reference 19

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Observation 8ed25b3f-7871-4b36-a88a-35ddbfa03bbe · outbound

This paper cites Mini-swe-agent,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Mini-swe-agent,

Reference 20

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Observation 570e181f-0f92-424b-a72d-1f3e38f439e4 · outbound

This paper cites Live-swe-agent: Can software engineering agents self-evolve on the fly?.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Live-swe-agent: Can software engineering agents self-evolve on the fly?

Reference 21

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Observation 98570e7d-9f54-48c9-afd6-5f2789d3e46c · outbound

This paper cites Context caching on disk,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Context caching on disk,

Reference 22

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Observation a0429276-3004-43b6-91e1-9e74e38a7bb3 · outbound

This paper cites Prompt caching,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Prompt caching,

Reference 23

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source=pdf_text observed=2026-08-01T14:11:54.608770Z digest=sha256:7396cf5fdd90f31c61a7afab26022084eae6df4b034aec7b4b28d57d25c609e1

Observation a564248d-9bdd-4dfd-bc2d-ce27ee09d46f · outbound

This paper cites Towards an understanding of large language models in software engineering tasks,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Towards an understanding of large language models in software engineering tasks,

Reference 24

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Observation 5b6db982-e5b6-4fe1-9059-ed8189ce890b · outbound

This paper cites Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks

Reference 25

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Observation 0e0c0f02-67d5-4670-bfa9-b181f08b84ac · outbound

This paper cites A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 26

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Observation ffbb8642-f274-4820-87e3-39b68852ec28 · outbound

This paper cites Towards an under- standing of context utilization in code intelligence,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Towards an under- standing of context utilization in code intelligence,

Reference 27

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Observation 2ad8dcfc-94b1-4e75-b702-af3bf2804ed0 · outbound

This paper cites Agents in software engineering: Survey, landscape, and vision,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Agents in software engineering: Survey, landscape, and vision,

Reference 28

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Observation 1a1e6471-0f43-408f-be92-73697253ec19 · outbound

This paper cites Adaptive-solver framework for dynamic strategy selection in large language model reasoning,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Adaptive-solver framework for dynamic strategy selection in large language model reasoning,

Reference 29

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Observation e48ca7d3-e796-4341-af7c-36e9a5eaa41e · outbound

This paper cites Identifying smart contract security issues in code snippets from stack overflow,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Identifying smart contract security issues in code snippets from stack overflow,

Reference 30

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Observation 5f52b62d-9567-490b-8c0f-f69b97ca560e · outbound

This paper cites Hyperion: Unveiling DApp Inconsistencies using LLM and Dataflow-Guided Symbolic Execution.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Hyperion: Unveiling DApp Inconsistencies using LLM and Dataflow-Guided Symbolic Execution

Reference 31

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Observation 56041003-2017-4d9c-8874-377dee69f8e1 · outbound

This paper cites SoTaNa: The Open-Source Software Development Assistant.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents SoTaNa: The Open-Source Software Development Assistant

Reference 32

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Observation 2674ed14-f096-44bf-8ee5-c9e60289621b · outbound

This paper cites Re- pomincoder: Improving repository-level code generation based on information loss screening,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Re- pomincoder: Improving repository-level code generation based on information loss screening,

Reference 33

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Observation 94f94113-059b-4ba0-980d-69823ec458eb · outbound

This paper cites Beyond functional correctness: Investigating coding style inconsistencies in large language models,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Beyond functional correctness: Investigating coding style inconsistencies in large language models,

Reference 34

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Observation e0ea7035-782e-4f98-b107-63d93e71f17e · outbound

This paper cites Top General Performance = Top Domain Performance? DomainCodeBench: A Multi-domain Code Generation Benchmark.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Top General Performance = Top Domain Performance? DomainCodeBench: A Multi-domain Code Generation Benchmark

Reference 35

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Observation e2e5439d-c944-4af2-ae2d-7318d75500ad · outbound

This paper cites Llm hallucinations in practical code gen- eration: Phenomena, mechanism, and mitigation,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Llm hallucinations in practical code gen- eration: Phenomena, mechanism, and mitigation,

Reference 36

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Observation cf445179-131f-4e19-b89d-5a56149ea7d0 · outbound

This paper cites S*: Test Time Scaling for Code Generation.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents S*: Test Time Scaling for Code Generation

Reference 37

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source=pdf_text observed=2026-08-01T14:11:55.463382Z digest=sha256:8fc7c043a34dd3ef870474dd9262d5384b30883eb382802d1a495100a52126b4

Observation c609dd5c-a15f-49bc-a80a-45d142a36396 · outbound

This paper cites CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings

Reference 38

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source=pdf_text observed=2026-08-01T14:11:55.543471Z digest=sha256:bc670f12b08b112147198beef7b84edc8267a0cf3901207954b9150ef54b2727

Observation c309acba-1609-4f5e-9bb8-28eba2131192 · outbound

This paper cites Design2code: Benchmarking multimodal code generation for automated front-end engineering,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Design2code: Benchmarking multimodal code generation for automated front-end engineering,

Reference 39

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source=pdf_text observed=2026-08-01T14:11:55.606053Z digest=sha256:891680bf7510c2d1d93f31d64bc02f53c75a997f56045f4217501884ae125011

Observation e77d0190-b8ca-4b9b-b466-eb8e27ebce49 · outbound

This paper cites What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond

Reference 40

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source=pdf_text observed=2026-08-01T14:11:55.656773Z digest=sha256:9d81f661b4bbcdfc2d3b8249ba80f9cd14ed74e611e7c7fecc43508489ea906a

Observation fcc88232-e5bc-4be6-b6ca-57436788537b · outbound

This paper cites Rmcbench: Benchmarking large language models’ resistance to malicious code,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Rmcbench: Benchmarking large language models’ resistance to malicious code,

Reference 41

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source=pdf_text observed=2026-08-01T14:11:55.732958Z digest=sha256:468c1ea45adc76744ed874831b203f19b1eed080c3d545879eaac9e9e130ae89

Observation d93ba1a4-9c8d-4fb5-87e6-87fc00b28b0e · outbound

This paper cites HumanEvo: An Evolution-aware Benchmark for More Realistic Evaluation of Repository-level Code Generation.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents HumanEvo: An Evolution-aware Benchmark for More Realistic Evaluation of Repository-level Code Generation

Reference 42

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source=pdf_text observed=2026-08-01T14:11:55.790898Z digest=sha256:4f09a1d3b0d03a7e91888616f98275fc82d335c9d24e32cbe268018e3108279d

Observation 54f96bda-f18a-48d3-a069-031c001c5fb3 · outbound

This paper cites Code completion by modeling flattened abstract syntax trees as graphs,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Code completion by modeling flattened abstract syntax trees as graphs,

Reference 43

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source=pdf_text observed=2026-08-01T14:11:55.842422Z digest=sha256:23f63e5d47000b01b19b8b4fb58cd8f565b9ed30c6c76cabb7455cfc0a138c75

Observation c909bc9a-50f8-42e0-b3ff-f509d3076c1e · outbound

This paper cites RLCoder: Reinforcement Learning for Repository-Level Code Completion.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents RLCoder: Reinforcement Learning for Repository-Level Code Completion

Reference 44

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source=pdf_text observed=2026-08-01T14:11:55.896587Z digest=sha256:1cd75a46492c9b28dbb8a0b4d7ee6d8ea990c8fd11b24b1507b27ded8e118082

Observation 0611c84f-5692-4149-b7a0-e7e4af6b127b · outbound

This paper cites Analogcoder: Analog circuit design via training-free code generation,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Analogcoder: Analog circuit design via training-free code generation,

Reference 45

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source=pdf_text observed=2026-08-01T14:11:55.971609Z digest=sha256:6c62ff82dc61f8c89c10b3d0c6498b1a3efe1474a967e5c73ca0eb42d1702585

Observation 37c91cbe-d58c-4b1c-9a52-18eae53c477e · outbound

This paper cites Domaineval: An auto-constructed benchmark for multi-domain code generation,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Domaineval: An auto-constructed benchmark for multi-domain code generation,

Reference 46

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source=pdf_text observed=2026-08-01T14:11:56.027006Z digest=sha256:b497d8f6fd8c0bcd3589b2c25ab9282bcc65deee956f03108d81751ea8b1749c

Observation e6381a6d-2d2a-4b1b-8c78-3249ded562e4 · outbound

This paper cites Unveiling the black box of plms with semantic anchors: towards interpretable neural semantic parsing,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Unveiling the black box of plms with semantic anchors: towards interpretable neural semantic parsing,

Reference 47

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source=pdf_text observed=2026-08-01T14:11:56.068643Z digest=sha256:bee99c67fa29d72ceb03865a2036e807adb83223ee78d9de2feeb6ebe026d51f

Observation 74504517-b149-42c0-9d3c-7b9c96684b05 · outbound

This paper cites Arkrepobench: A repository-level code completion benchmark for harmonyos development,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Arkrepobench: A repository-level code completion benchmark for harmonyos development,

Reference 48

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source=pdf_text observed=2026-08-01T14:11:56.121088Z digest=sha256:46e5b51340092a08df6c4c031bcecc01da37be62b4b85b7f044bee6aeb6bae34

Observation a0609919-2b8a-4d07-bca2-b06439291eb6 · outbound

This paper cites Realsec-bench: A benchmark for evaluating secure code generation in real-world repositories,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Realsec-bench: A benchmark for evaluating secure code generation in real-world repositories,

Reference 49

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source=pdf_text observed=2026-08-01T14:11:56.180005Z digest=sha256:bd5d2193259de9459f58f4d285688e56de4647f60a36c3261333e1c3a85c671c

Observation 668fc869-3607-4dc1-ade7-0fdf0a21fc02 · outbound

This paper cites SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing

Reference 50

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source=pdf_text observed=2026-08-01T14:11:56.235998Z digest=sha256:de338c2e2fed46cbfdde1689c7de46d445c0623c871815d15eba274807fdb98d

Observation 8819e3f7-fc7e-49fa-a9a1-1427016af770 · outbound

This paper cites Spencer: Self-adaptive model distillation for efficient code retrieval,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Spencer: Self-adaptive model distillation for efficient code retrieval,

Reference 51

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source=pdf_text observed=2026-08-01T14:11:56.284913Z digest=sha256:50534221f0de1075e671036f0d883f6c2659b675b6366463a12b6429dd161d9d

Observation bf782b05-f368-4aee-b7dc-8e79762515e0 · outbound

This paper cites Cosqa+: Enhancing code search evaluation with a multi-choice bench- mark and test-driven agents,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Cosqa+: Enhancing code search evaluation with a multi-choice bench- mark and test-driven agents,

Reference 52

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source=pdf_text observed=2026-08-01T14:11:56.338049Z digest=sha256:7f6b7a7afcfa421e93f2bfa62dd990caddb394a3c88c5abe0dc10c7d262faf39

Observation c11db400-e010-4e9f-9c8a-f8518278a235 · outbound

This paper cites Accelerating code search with deep hashing and code classification,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Accelerating code search with deep hashing and code classification,

Reference 53

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source=pdf_text observed=2026-08-01T14:11:56.391879Z digest=sha256:4e3588acb82ee7b2f65d8a771fe348bc3a3e1b650925d95e3a83317c00a56cf1

Observation 9f54634c-661a-4902-8179-44066ef9a190 · outbound

This paper cites Revisiting code search in a two-stage paradigm,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Revisiting code search in a two-stage paradigm,

Reference 54

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source=pdf_text observed=2026-08-01T14:11:56.450427Z digest=sha256:f77c0c1e6556f9b6024388a7013587ec37fd03d7c35996cb6afa1a3cd9e0ec3f

Observation 62e4f3da-b4b5-42ac-8740-e3d5cf5fda03 · outbound

This paper cites Cocosoda: Effective contrastive learning for code search,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Cocosoda: Effective contrastive learning for code search,

Reference 55

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source=pdf_text observed=2026-08-01T14:11:56.502442Z digest=sha256:f0316526be1e2f50c5fb9ca18c796f5cd90e1a5ede473ad2d3e6c9171be322fd

Observation 8d5b5c2f-745e-4595-ab8c-3399380b39f1 · outbound

This paper cites Rethinking Negative Pairs in Code Search.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Rethinking Negative Pairs in Code Search

Reference 56

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source=pdf_text observed=2026-08-01T14:11:56.546388Z digest=sha256:d61a776cd11dcac3d9c61d35d61e498a0453e2274f6e0aaa4bbd2928cf9dd025

Observation 5ac1c873-fc8c-4b85-be07-10643f3c8fa0 · outbound

This paper cites Who needs the most research effort? investigating the importance of smart contract weaknesses,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Who needs the most research effort? investigating the importance of smart contract weaknesses,

Reference 57

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source=pdf_text observed=2026-08-01T14:11:56.595864Z digest=sha256:b1c8aa98d20b1938c3854029dc5b41078d918274b70ab522b5ce5e17aec9d816

Observation 9a6590ca-0c21-4c84-8e3e-cf7128d0a985 · outbound

This paper cites You augment me: Exploring chatgpt- based data augmentation for semantic code search,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents You augment me: Exploring chatgpt- based data augmentation for semantic code search,

Reference 58

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source=pdf_text observed=2026-08-01T14:11:56.671608Z digest=sha256:24c5254b7fbbac227939f3ed6680147fe9714205526cda2f9f101f056297ee70

Observation 1fdbf8fd-6a28-475e-a979-9c4eaf0ddc2e · outbound

This paper cites Tackling long code search with splitting, encoding, and aggregating,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Tackling long code search with splitting, encoding, and aggregating,

Reference 59

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source=pdf_text observed=2026-08-01T14:11:56.738994Z digest=sha256:306a37da09dc8715d5cbd7f391247871d1a49a18e14702816cb13e66b37b394a

Observation c1871c59-431f-42e7-8a5d-c1dd9110819d · outbound

This paper cites Improving code search with hard negative sampling based on fine-tuning,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Improving code search with hard negative sampling based on fine-tuning,

Reference 60

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source=pdf_text observed=2026-08-01T14:11:56.791622Z digest=sha256:d051eee8ec17e31b17fbe4b6139c9c94799a800f284bda07e3756165e3d9096e

Observation 276167ed-3e2b-4635-855d-ff800f8b6c33 · outbound

This paper cites Costv: Accelerating code search with two-stage paradigm and vector retrieval,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Costv: Accelerating code search with two-stage paradigm and vector retrieval,

Reference 61

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source=pdf_text observed=2026-08-01T14:11:56.871575Z digest=sha256:d9e97c7feca64ec6109e285209b3b090011de52047e86ae913940af95adbc739

Observation 01c9beca-cbcd-4d90-aeaa-69d19f66b385 · outbound

This paper cites Search-o1: Agentic Search-Enhanced Large Reasoning Models.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Search-o1: Agentic Search-Enhanced Large Reasoning Models

Reference 62

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source=pdf_text observed=2026-08-01T14:11:56.956797Z digest=sha256:e3d7573d720535bf17d39908707bee07424a9eb6b033f7d304757ecbe193982a

Observation f6ba565c-3bbb-403a-b056-c9355f26706c · outbound

This paper cites An empirical study on code search pre-trained models: Academic progresses vs. industry requirements,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents An empirical study on code search pre-trained models: Academic progresses vs. industry requirements,

Reference 63

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source=pdf_text observed=2026-08-01T14:11:56.966769Z digest=sha256:de45eb0030ca8fe3d966167c7585af1e47a5eaba79d27c9e64b8a9255b2a2203

Observation 2781d2b6-d427-42bb-94d9-730f6b753af0 · outbound

This paper cites En- riching query semantics for code search with reinforcement learning,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents En- riching query semantics for code search with reinforcement learning,

Reference 64

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source=pdf_text observed=2026-08-01T14:11:57.149414Z digest=sha256:15ef84410b44b673fee051e2d75893c30ccda2626b35101960d81b0d7dad83e4

Observation 44bca06f-094e-4f87-b626-02782a9cc27d · outbound

This paper cites Are Decoder-Only Large Language Models the Silver Bullet for Code Search?.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Are Decoder-Only Large Language Models the Silver Bullet for Code Search?

Reference 65

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source=pdf_text observed=2026-08-01T14:11:57.323146Z digest=sha256:516fea9b209040e01d4166c45cf954ee84dfde82fa66cc39d45c5020094f4b77

Observation 422d5e27-6069-4f0e-bf2d-948684d3a8fb · outbound

This paper cites Code Search Debiasing:Improve Search Results beyond Overall Ranking Performance.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Code Search Debiasing:Improve Search Results beyond Overall Ranking Performance

Reference 66

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T14:11:57.539775Z digest=sha256:6eadd2746d220d8659325a9cc5f280533300f639a9618673813b8854973c2e44

Observation 62a7b43e-ba9e-47d0-bdb1-70303d4f50bf · outbound

This paper cites Omnigirl: A multilingual and multimodal benchmark for github issue resolution,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Omnigirl: A multilingual and multimodal benchmark for github issue resolution,

Reference 67

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source=pdf_text observed=2026-08-01T14:11:57.661605Z digest=sha256:90fbe244395ec20d85eeab660dd2d7daa52bc39a7794b98089f30a79d5566ad4

Observation 6a101107-6bd7-42ac-8644-744678aa47d2 · outbound

This paper cites Magis: Llm-based multi-agent framework for github issue resolution,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Magis: Llm-based multi-agent framework for github issue resolution,

Reference 68

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source=pdf_text observed=2026-08-01T14:11:57.805872Z digest=sha256:d7b5ae80793dd6f6dd3190ac09a477665a0298d89b0e4f571be9ee38c2119034

Observation 02cddc3a-c494-4859-9d91-4eeb08fd654d · outbound

This paper cites Swe-exp: Experience-driven software issue resolution,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Swe-exp: Experience-driven software issue resolution,

Reference 69

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source=pdf_text observed=2026-08-01T14:11:57.953806Z digest=sha256:99eaf3d09df342df361672b4ea95cb46b225247db6705af037f26d3030f3b767

Observation ac013a08-fa25-4203-875d-c593005f154a · outbound

This paper cites Alibaba lingmaagent: Improving automated issue resolution via comprehensive repository exploration,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Alibaba lingmaagent: Improving automated issue resolution via comprehensive repository exploration,

Reference 70

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source=pdf_text observed=2026-08-01T14:11:58.195530Z digest=sha256:209d1356d4361a0547f42c7205bc1199edf686eecde714853c150bf165a54da1

Observation a81c09f3-fd5d-40a8-99f9-ccdbf8df7f1c · outbound

This paper cites SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution

Reference 71

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source=pdf_text observed=2026-08-01T14:11:58.347513Z digest=sha256:5e36b410a55d5ce1009bd791dc34a4f943eb10dbe37e4309844742cc9a2d81ae

Observation 2370ef1a-7e5a-4fb0-a605-fd0265ccd270 · outbound

This paper cites SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution

Reference 72

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T14:11:58.501423Z digest=sha256:50cae8acd19843938d7bb079dff7fd317d08a0330829d5f31fa5836f97bbf336

Observation 17283813-bb2d-4290-acc1-9d759e698689 · outbound

This paper cites Prometheus: Unified knowledge graphs for issue resolution in multilingual codebases,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Prometheus: Unified knowledge graphs for issue resolution in multilingual codebases,

Reference 73

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source=pdf_text observed=2026-08-01T14:11:58.678384Z digest=sha256:9fc50e0c26e8d8b24c8db3b2825ad344fdace73ed3436dab215d76c03e8938c3

Observation 60657ef9-552e-4d96-86ec-a1406894df9c · outbound

This paper cites Swe data construction, automatically!.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Swe data construction, automatically!

Reference 74

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source=pdf_text observed=2026-08-01T14:11:58.846280Z digest=sha256:71f786b841c1f8bcc21e05f1c377d4eb3a91b4bf4f88ab694039e3a3588f9d56

Observation e4b25bac-79f9-4860-a009-8ad5e32b8b49 · outbound

This paper cites On the evaluation of neural code summarization,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents On the evaluation of neural code summarization,

Reference 75

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T14:11:58.994107Z digest=sha256:35be7436d2cf5baf9a1a08a47aaf903ff504ac968e27380c97c29ef0a76d2b06

Observation d4151bd0-a520-4614-8524-669fc0ac5629 · outbound

This paper cites CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees

Reference 76

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source=pdf_text observed=2026-08-01T14:11:59.140440Z digest=sha256:1a7ba2433fca868545347359852a5c094bb03b4b9308e346bfc704c5b4cda87c

Observation 125b0da6-8223-4cca-83a5-ad51c24eeaf9 · outbound

This paper cites Repotransbench: A real-world benchmark for repository-level code translation,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Repotransbench: A real-world benchmark for repository-level code translation,

Reference 77

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source=pdf_text observed=2026-08-01T14:11:59.300096Z digest=sha256:cf30bdf0e613ed481add7dad19a0e3003bfc483feff237036407cb50a113fa0b

Observation c9bad06d-caa8-429d-8657-0a49443bca18 · outbound

This paper cites Repository- level code translation benchmark targeting rust,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Repository- level code translation benchmark targeting rust,

Reference 78

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source=pdf_text observed=2026-08-01T14:11:59.448952Z digest=sha256:606173944c4e6b22cb2ff1bf44b8b9f69a07881bcd37228b0c30fc2a9f7206b5

Observation 4de93ff4-e0e9-4031-aa7d-23c75352227c · outbound

This paper cites Lost in translation: A study of bugs introduced by large language models while translating code,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Lost in translation: A study of bugs introduced by large language models while translating code,

Reference 79

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source=pdf_text observed=2026-08-01T14:11:59.532497Z digest=sha256:ac4d730a20cfcaeb97b5b5f791f7fda5dfcc47057024115c0a4afb96937f5504

Observation cab8b2a0-b109-4f23-bc73-d713e5b45fe5 · outbound

This paper cites Unraveling the potential of large language models in code translation: How far are we?.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Unraveling the potential of large language models in code translation: How far are we?

Reference 80

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source=pdf_text observed=2026-08-01T14:11:59.689065Z digest=sha256:89cbb31048052ce308d3981768307940b3f3b30e8da9accb1222d23e6b6339e8

Observation 7c904305-f574-4f0a-ac34-50f7ad04afe8 · outbound

This paper cites CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation

Reference 81

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source=pdf_text observed=2026-08-01T14:11:59.838247Z digest=sha256:0250e573b038303f574a0adb782bbb51fcaf0fa972125a620be8a74662b57366

Observation 7c50b126-a07b-49be-94db-6158a97f001a · outbound

This paper cites A large-scale empirical study of commit message genera- tion: models, datasets and evaluation,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents A large-scale empirical study of commit message genera- tion: models, datasets and evaluation,

Reference 82

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source=pdf_text observed=2026-08-01T14:11:59.978495Z digest=sha256:8f076af82b3f07d56015d8e098901376c6339d7168cb1d95c92cacb2d2aa1737

Observation b6c50092-462c-4b0f-b260-6539db5f8ce3 · outbound

This paper cites Kadel: Knowledge-aware denoising learning for commit message generation,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Kadel: Knowledge-aware denoising learning for commit message generation,

Reference 83

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no resolver link, observed 2026-08-01T14:12:00.094698Z

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source=pdf_text observed=2026-08-01T14:12:00.094698Z digest=sha256:1bb73a03e9c939a41523e2b2919f15ddceeca8f7001f8dcfea47e784d506232b

Observation b40ab3a9-da69-43c1-88e8-fa46c372d506 · outbound

This paper cites Automated commit message generation with large language models: An empirical study and beyond,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Automated commit message generation with large language models: An empirical study and beyond,

Reference 84

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source=pdf_text observed=2026-08-01T14:12:00.204507Z digest=sha256:5051be18441dfe7145e6332bc064ceff515589267114cfc80db8f0da09450c8a

Observation 63aff878-8793-4595-824f-769e8c247963 · outbound

This paper cites Using large language models for commit message generation: A preliminary study,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Using large language models for commit message generation: A preliminary study,

Reference 85

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source=pdf_text observed=2026-08-01T14:12:00.358737Z digest=sha256:65a3ac301087ff41019d4f500c31785360f2087b297223660737f2d06bc12271

Observation c142cfd5-3e82-469b-a0eb-4d677a2402cf · outbound

This paper cites Au- tomatic commit message generation: A critical review and directions for future work,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Au- tomatic commit message generation: A critical review and directions for future work,

Reference 86

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source=pdf_text observed=2026-08-01T14:12:00.475034Z digest=sha256:525563416133d7fe022bac259ed8cf62256a8b505ced1b8ea0126658eb96b2fc

Observation 3468e9e5-fcfc-4c0c-a7d0-5a8a18fb1a1f · outbound

This paper cites On the evaluation of commit message generation models: An experimental study,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents On the evaluation of commit message generation models: An experimental study,

Reference 87

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source=pdf_text observed=2026-08-01T14:12:00.595451Z digest=sha256:08247b6d41fd7ce762897992c69d5b609d428b3d50f27d3b03c982a70c15ffe4

Observation 45eb2eb8-e6a2-45bf-a504-5e9a1d6730a2 · outbound

This paper cites RACE: Retrieval-Augmented Commit Message Generation.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents RACE: Retrieval-Augmented Commit Message Generation

Reference 88

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source=pdf_text observed=2026-08-01T14:12:00.723646Z digest=sha256:6fd08545fc07f5bad4efef76497b83febfdb2630009113343d142dfbd899f088

Observation 7510374a-b3d2-476d-88f8-54df8d96bd9f · outbound

This paper cites Snippet comment generation based on code context expan- sion,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Snippet comment generation based on code context expan- sion,

Reference 89

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source=pdf_text observed=2026-08-01T14:12:00.811582Z digest=sha256:5e515ae0ea0cbce55359e9a4fcea05739b7555138d50cd19d0e1614e67141bfb

Observation 76e29a1f-67fd-4d61-b636-4d5de1e35b9e · outbound

This paper cites Ealink: An efficient and accurate pre-trained framework for issue-commit link recovery,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Ealink: An efficient and accurate pre-trained framework for issue-commit link recovery,

Reference 90

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source=pdf_text observed=2026-08-01T14:12:00.911486Z digest=sha256:92d638e32997706fc2966fd0c1eb09eac1508a590907a6eeaeb2ef0ca20f226a

Observation 544f72ac-d680-4add-8842-a7ca1391e912 · outbound

This paper cites Sparsecoder: Identifier-aware sparse transformer for file-level code summarization,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Sparsecoder: Identifier-aware sparse transformer for file-level code summarization,

Reference 91

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source=pdf_text observed=2026-08-01T14:12:00.982007Z digest=sha256:b881e4d06a1b07803b32009443ca6a42373c41e73609473d6387aa205ebc0697

Observation 63b40b3f-02a9-4a5d-b76f-30c5bb958554 · outbound

This paper cites When to stop? towards efficient code generation in llms with excess token prevention,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents When to stop? towards efficient code generation in llms with excess token prevention,

Reference 92

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source=pdf_text observed=2026-08-01T14:12:00.985293Z digest=sha256:d20e5b8346a27ebe28f3a5c21144b99a5a87ca576e02d04cef122006eab13f9d

Observation c7788802-3e52-49ae-a5dc-6755bb5d9922 · outbound

This paper cites Longcoder: A long-range pre-trained language model for code completion,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Longcoder: A long-range pre-trained language model for code completion,

Reference 93

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source=pdf_text observed=2026-08-01T14:12:00.988084Z digest=sha256:fd4dd56d1aa594df62c6e1e63dcfea07c8b42a42d647c571b69369b240879316

Observation e47682a3-d94b-4844-89a0-209d6dbf2410 · outbound

This paper cites Prompt cache: Modular attention reuse for low-latency inference,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Prompt cache: Modular attention reuse for low-latency inference,

Reference 94

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source=pdf_text observed=2026-08-01T14:12:00.990964Z digest=sha256:fa347097f096d5f32046bb1e9ae9b1573d157d790b9bbfa93a4f6e35ab7b11ba

Observation dc0e40d2-bd2a-4043-8476-b901e82db1d6 · outbound

This paper cites PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling

Reference 95

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source=pdf_text observed=2026-08-01T14:12:00.993898Z digest=sha256:5361b0dbd8c2c506226a3d3a0ba6a696a03c63040d79e798b0c04d615b821fcd

Observation 85915596-fc29-44b7-9cc9-dcaf28810ac3 · outbound

This paper cites WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More

Reference 96

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no resolver link, observed 2026-08-01T14:12:00.997267Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-01T14:12:00.997267Z digest=sha256:fe42b119ce2adbd9bf2915ab5a6ffa48ac79525c5fe0c2d546222805cf9d6ac3

Observation e5f68943-dc4d-448c-b85b-5c1cd7d85bf5 · outbound

This paper cites Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference

Reference 97

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source=pdf_text observed=2026-08-01T14:12:01.001000Z digest=sha256:51e8a3a0b282e4fff3da2cedd98ca3a95bc75a12796535cc10fffe7bfdbbb405

Observation edb250bc-a214-4539-8d84-1a4b1966f544 · outbound

This paper cites From logical to computational sparsity: Structure-aware block-sparse attention for long-code completion,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents From logical to computational sparsity: Structure-aware block-sparse attention for long-code completion,

Reference 98

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source=pdf_text observed=2026-08-01T14:12:01.004449Z digest=sha256:f6adb71847dc9f14adfd71bde2bf80286062437ac98bee90a693fb48e3ab2fd6

Observation 8b634790-d714-49cb-abc3-3be89817d4ca · outbound

This paper cites Longbench: A bilingual, multitask benchmark for long context understanding,.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents Longbench: A bilingual, multitask benchmark for long context understanding,

Reference 99

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source=pdf_text observed=2026-08-01T14:12:01.007531Z digest=sha256:6ad49756ecce30a3a5fc40153d591774fe07aed8ed8a2fe3393616972f48420c

Observation 39c128bb-a90b-4965-8ae5-b6671f44f51e · outbound

This paper cites CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network

Reference 100

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source=pdf_text observed=2026-08-01T14:12:01.010734Z digest=sha256:55cda5e308fc1df45d2e7cfd326d9087792bfc7a67070132c2762f578c61a8b8

Pith citing papers

No inbound Pith citation observations are available.