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Paper Citation Record · LEDGER

Antares: Foundation Models for Agentic Vulnerability Localization

As of 9 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 0 inbound Pith citation observations for arXiv:2608.02407.

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

pith.paper-citation-record.v1
2608.02407 v1

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:50:50.779900Z

measured 78 of 78 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

78 of 78 outbound references displayed

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  • verified fuzzy0
  • unresolved75
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

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Outbound references

Observation 8848ad00-0978-448f-8d2f-90257fdb5331 · outbound

This paper cites CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence.

Antares: Foundation Models for Agentic Vulnerability Localization CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence

Reference 1

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source=pdf_text observed=2026-08-04T07:50:50.560574Z digest=sha256:07176abd164f201ad2e685769a7f6892aeeb96faaa774707bbc11c0a0dc3a060

Observation fc74c6e4-b04b-4c1d-85ac-1dd72da47c4f · outbound

This paper cites False negative - that one is going to kill you.

Antares: Foundation Models for Agentic Vulnerability Localization False negative - that one is going to kill you

Reference 2

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source=pdf_text observed=2026-08-04T07:50:50.564612Z digest=sha256:ed156c134b2b8a394a5ff27d97a58cb91cc6f940a6e141d163558e9015cef226

Observation d1aabaed-9d0f-4441-8150-cff376af8797 · outbound

This paper cites Claude code.

Antares: Foundation Models for Agentic Vulnerability Localization Claude code

Reference 3

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source=pdf_text observed=2026-08-04T07:50:50.567465Z digest=sha256:ceab96d008e3c01b0e79a3e9a7b8e62fb36d85f6a15433f546a5540a8c0e6a25

Observation 57d4b434-ed66-4ca0-b40d-7b11c875a33e · outbound

This paper cites Cursor: The ai code editor.

Antares: Foundation Models for Agentic Vulnerability Localization Cursor: The ai code editor

Reference 4

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Observation f08401bb-8d98-4eb5-9dde-313eb322b720 · outbound

This paper cites URL https://arxiv.org/abs/2506 .07982.

Antares: Foundation Models for Agentic Vulnerability Localization URL https://arxiv.org/abs/2506 .07982

Reference 5

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source=pdf_text observed=2026-08-04T07:50:50.573294Z digest=sha256:6e15277fc7cd9b7a45c8cfb70becbee1c936004a8bce3babb4e5ed414c005ab3

Observation 77950e1e-156e-4beb-a718-faccb3fe765e · outbound

This paper cites Agenticscr: An autonomous agentic secure code review for immature vulnerabilities detection, 2026.

Antares: Foundation Models for Agentic Vulnerability Localization Agenticscr: An autonomous agentic secure code review for immature vulnerabilities detection, 2026

Reference 6

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source=pdf_text observed=2026-08-04T07:50:50.576245Z digest=sha256:346a24cfbd653f3fe2539378564daf8c8db0831d0bacd735904683970497ce28

Observation 2e3191f9-f046-4c3e-94e1-b235646cf392 · outbound

This paper cites Vulnerability localization benchmark.

Antares: Foundation Models for Agentic Vulnerability Localization Vulnerability localization benchmark

Reference 7

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source=pdf_text observed=2026-08-04T07:50:50.579377Z digest=sha256:5c4009825a5088bb217d2cb32923c9a82264b4ef1e9827e9f087d5338f3c775f

Observation fd1a79e0-8fd4-4488-b87d-eea46d92e674 · outbound

This paper cites Composer: Building a fast frontier model with rl.

Antares: Foundation Models for Agentic Vulnerability Localization Composer: Building a fast frontier model with rl

Reference 8

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source=pdf_text observed=2026-08-04T07:50:50.581904Z digest=sha256:bfc3186d265739eda5a1b3ae5635852c6e667929433a1ec77c7902cac158ed0e

Observation 0eb7597c-dc67-46bc-833c-82e0bb977adc · outbound

This paper cites Rader: Reasoning-aware dense retrieval models,.

Antares: Foundation Models for Agentic Vulnerability Localization Rader: Reasoning-aware dense retrieval models,

Reference 9

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source=pdf_text observed=2026-08-04T07:50:50.584382Z digest=sha256:403588a6fb338c7130d98185db2e45129fc744146777956d0f8fa437328c106f

Observation 44a65f56-2427-4dac-b4b9-b7efc9ad8df0 · outbound

This paper cites Deephat-v1-7b.

Antares: Foundation Models for Agentic Vulnerability Localization Deephat-v1-7b

Reference 10

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Observation d7163c7d-a53c-4912-8908-b2d075ceb55c · outbound

This paper cites SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?.

Antares: Foundation Models for Agentic Vulnerability Localization SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?

Reference 11

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Observation 40c4562f-8b9e-45d8-991b-b25fae8cd1b9 · outbound

This paper cites Codeql: Semantic code analysis.

Antares: Foundation Models for Agentic Vulnerability Localization Codeql: Semantic code analysis

Reference 12

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source=pdf_text observed=2026-08-04T07:50:50.596503Z digest=sha256:503845f8e83b60274fad794b9f06f8e2d04230cd8f35f637e7068732e648631f

Observation 8278c662-75f8-4fa4-801e-c12cd65d7585 · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 13

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Observation 523673ea-ff9c-4850-a509-b9847261e1c8 · outbound

This paper cites RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing.

Antares: Foundation Models for Agentic Vulnerability Localization RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing

Reference 14

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source=pdf_text observed=2026-08-04T07:50:50.602352Z digest=sha256:befa2e0ba56d9cae9aa1246a1ffc8a77962a86d4b87c41e0f204abe8572ffff1

Observation 04800b93-b488-400b-8b8c-5275737c2aaf · outbound

This paper cites Granite-4.0-1b.

Antares: Foundation Models for Agentic Vulnerability Localization Granite-4.0-1b

Reference 15

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Observation 874f72ff-2878-4ccb-a51d-f8b0e602ce2c · outbound

This paper cites Granite-4.0-350m.

Antares: Foundation Models for Agentic Vulnerability Localization Granite-4.0-350m

Reference 16

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source=pdf_text observed=2026-08-04T07:50:50.610966Z digest=sha256:266544f47cbf0e2c1318ae715cc6a1e2c2577ab71c80219c5642dbeba319c061

Observation bb1d3362-5aac-4721-a6ed-3657e4257016 · outbound

This paper cites Accessed: 2026-06-29.

Antares: Foundation Models for Agentic Vulnerability Localization Accessed: 2026-06-29

Reference 17

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Observation 66eede6c-6805-46ab-9fe2-2b26494c7459 · outbound

This paper cites Kakade, and Carles Domingo-Enrich.

Antares: Foundation Models for Agentic Vulnerability Localization Kakade, and Carles Domingo-Enrich

Reference 18

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source=pdf_text observed=2026-08-04T07:50:50.616289Z digest=sha256:036bcdbf7910e93ebbe7700e84f18d6ead6426945cffe80426215f1ecc5d0a52

Observation d99869a4-d93c-429d-bf3f-ac45890e898a · outbound

This paper cites Granite-4.0-micro.

Antares: Foundation Models for Agentic Vulnerability Localization Granite-4.0-micro

Reference 19

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source=pdf_text observed=2026-08-04T07:50:50.613590Z digest=sha256:f601e013d3726a4fb15c536b59fc43fc5671ba3ea2b21a2d1e486a68591066c7

Observation d0bb8e6f-dc37-487f-b6ee-83b9861e86dc · outbound

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

Antares: Foundation Models for Agentic Vulnerability Localization SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 20

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source=pdf_text observed=2026-08-04T07:50:50.621488Z digest=sha256:88667af09216c33c772689579e4e8faa124c129ba533acf618941f2caae18cff

Observation 4ac43929-65a7-4c0b-a76d-0c1212d43599 · outbound

This paper cites DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning.

Antares: Foundation Models for Agentic Vulnerability Localization DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning

Reference 21

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source=pdf_text observed=2026-08-04T07:50:50.618709Z digest=sha256:35e3aa9237bf81d9921e8ef8729bd877bf0a6e27f4b15cd2deee52ea3e922199

Observation aeda815f-13a4-4c4d-ae86-1fcd292ebe89 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Antares: Foundation Models for Agentic Vulnerability Localization Dense Passage Retrieval for Open-Domain Question Answering

Reference 22

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source=pdf_text observed=2026-08-04T07:50:50.627362Z digest=sha256:4c6567eef84ae3716a9f978a8c567ad2880e6dbac6f4e56e5833fb072c4c8b0c

Observation 840835ea-d8f0-4fbf-9f1d-c3769136813b · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

Antares: Foundation Models for Agentic Vulnerability Localization Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 23

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source=pdf_text observed=2026-08-04T07:50:50.624294Z digest=sha256:130fcc41845d0cf9566142bae3c11056a757f8d42f139aa588734851dd16fb72

Observation cd1943aa-0ed0-404f-8365-2caf563bf3d7 · outbound

This paper cites FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelines.

Antares: Foundation Models for Agentic Vulnerability Localization FAPO: Fully Automated Prompt Optimization of Multi-Step LLM Pipelines

Reference 24

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Observation 4e9ef4b4-22af-40d3-b758-29e49076fb20 · outbound

This paper cites Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report.

Antares: Foundation Models for Agentic Vulnerability Localization Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report

Reference 25

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Observation 27aae124-0167-4a63-aeb1-87c315cb7894 · outbound

This paper cites Openresearcher: A fully open pipeline for long-horizon deep research trajectory synthesis, 2026.

Antares: Foundation Models for Agentic Vulnerability Localization Openresearcher: A fully open pipeline for long-horizon deep research trajectory synthesis, 2026

Reference 26

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Observation 21ca57f0-2920-46c7-a6a9-e328cebcea3c · outbound

This paper cites Webthinker: Empowering large reasoning models with deep research capability,.

Antares: Foundation Models for Agentic Vulnerability Localization Webthinker: Empowering large reasoning models with deep research capability,

Reference 27

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Observation e604d45e-9b70-4fb0-90f8-796e49b5fe7b · outbound

This paper cites WebThinker: Empowering Large Reasoning Models with Deep Research Capability.

Antares: Foundation Models for Agentic Vulnerability Localization WebThinker: Empowering Large Reasoning Models with Deep Research Capability

Reference 28

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Observation 6d04b26d-69f4-4cb1-9e55-6f67531be454 · outbound

This paper cites Vulnllm-r: Specialized reasoning llm with agent scaffold for vulnerability detection,.

Antares: Foundation Models for Agentic Vulnerability Localization Vulnllm-r: Specialized reasoning llm with agent scaffold for vulnerability detection,

Reference 29

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Observation 42f49427-0441-483c-8b9c-2cfe65debb2a · outbound

This paper cites Synthesizing Multi-Agent Harnesses for Vulnerability Discovery.

Antares: Foundation Models for Agentic Vulnerability Localization Synthesizing Multi-Agent Harnesses for Vulnerability Discovery

Reference 30

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Observation ed635049-b67c-454c-8bcf-989f0c9f2db6 · outbound

This paper cites The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence.

Antares: Foundation Models for Agentic Vulnerability Localization The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence

Reference 31

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Observation 495158a3-af4f-4663-8731-0507abbce42f · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

Antares: Foundation Models for Agentic Vulnerability Localization gpt-oss-120b & gpt-oss-20b Model Card

Reference 32

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Observation 82a888c1-cfb7-4718-9338-b669daf85f36 · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 33

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Observation 14819b50-598f-4516-9275-98adfde75b12 · outbound

This paper cites Introducing swe-bench verified.

Antares: Foundation Models for Agentic Vulnerability Localization Introducing swe-bench verified

Reference 34

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Observation 688cb50c-975d-4ce1-8682-93663ac085f6 · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 35

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Observation bb547589-42e8-4062-bade-4accb6f291c4 · outbound

This paper cites A practical approach to the automatic classification of security-relevant commits.

Antares: Foundation Models for Agentic Vulnerability Localization A practical approach to the automatic classification of security-relevant commits

Reference 36

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Observation 5ee85150-b3ea-43ee-bd7c-abc77d2ba859 · outbound

This paper cites Introducing swe-grep and swe-grep-mini: Rl for multi-turn, fast context retrieval.

Antares: Foundation Models for Agentic Vulnerability Localization Introducing swe-grep and swe-grep-mini: Rl for multi-turn, fast context retrieval

Reference 37

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Observation 4c6f3c30-bdb5-4cf5-b0df-9beb02d1a9c5 · outbound

This paper cites Gonzalez.

Antares: Foundation Models for Agentic Vulnerability Localization Gonzalez

Reference 38

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Observation 7a94227a-af5c-4658-ba7a-75789f84180d · outbound

This paper cites TongSearch-QR: Reinforced Query Reasoning for Retrieval.

Antares: Foundation Models for Agentic Vulnerability Localization TongSearch-QR: Reinforced Query Reasoning for Retrieval

Reference 39

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Observation f3775eb6-c352-426a-a27c-e9ac922bc5f3 · outbound

This paper cites ReasonIR: Training Retrievers for Reasoning Tasks.

Antares: Foundation Models for Agentic Vulnerability Localization ReasonIR: Training Retrievers for Reasoning Tasks

Reference 40

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source=pdf_text observed=2026-08-04T07:50:50.685326Z digest=sha256:521f3c2d1df614c4eb94c76f6ef597386fcd5004e9d7ce90d796e4e386255dbe

Observation 5d1d1260-3655-48fb-91a6-5017c8f2b337 · outbound

This paper cites Lily-Cybersecurity-7B-v0.2.

Antares: Foundation Models for Agentic Vulnerability Localization Lily-Cybersecurity-7B-v0.2

Reference 41

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Observation 39ca3cff-cd70-4071-a113-be70cc0d458b · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 42

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Observation b62f91e6-9de3-4e1c-8460-edc37fea8a3c · outbound

This paper cites NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security.

Antares: Foundation Models for Agentic Vulnerability Localization NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security

Reference 43

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source=pdf_text observed=2026-08-04T07:50:50.682477Z digest=sha256:71803a82ac19778aee9772a0da3a7bcc948d811a2f64cbf7e2256b24946f8707

Observation 9174a809-5a58-4328-bad5-5185e748a007 · outbound

This paper cites Sonarqube.

Antares: Foundation Models for Agentic Vulnerability Localization Sonarqube

Reference 44

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source=pdf_text observed=2026-08-04T07:50:50.696935Z digest=sha256:ce7f40aa85da5c7c2a6bab2f4de60d922c1c9f7bdc07031cf0b76b1dd54c2b26

Observation 48170847-7849-4c6c-b01f-98eac3a99fbd · outbound

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

Antares: Foundation Models for Agentic Vulnerability Localization DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 45

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Observation 02c76d80-eb57-4f4d-9fb4-e41670603165 · outbound

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

Antares: Foundation Models for Agentic Vulnerability Localization HybridFlow: A Flexible and Efficient RLHF Framework

Reference 46

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Observation 1a737a19-6529-47c4-a83e-b5a353f1b3d0 · outbound

This paper cites ECHO: Terminal Agents Learn World Models for Free.

Antares: Foundation Models for Agentic Vulnerability Localization ECHO: Terminal Agents Learn World Models for Free

Reference 47

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source=pdf_text observed=2026-08-04T07:50:50.693796Z digest=sha256:ff1ec9e2840fea0d18bf33b37bb3c8acf388802dff13bb04e491190879eb2441

Observation d1a1727b-e726-499e-aa25-31d8aa971ff5 · outbound

This paper cites Falcon-h1r: Pushing the reasoning frontiers with a hybrid model for efficient test-time scaling,.

Antares: Foundation Models for Agentic Vulnerability Localization Falcon-h1r: Pushing the reasoning frontiers with a hybrid model for efficient test-time scaling,

Reference 48

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source=pdf_text observed=2026-08-04T07:50:50.710566Z digest=sha256:0b5f8ac5bcb10721eb7df2ca843591e8ca4c93f7eff8e900a6af4cdb4fc8c2d6

Observation b8e16f2f-08d2-451b-8abd-5c590a79100b · outbound

This paper cites Granite 4.0 nano: Just how small can you go? https://huggin gface.co/blog/ibm-granite/granite-4-nano , October 2025.

Antares: Foundation Models for Agentic Vulnerability Localization Granite 4.0 nano: Just how small can you go? https://huggin gface.co/blog/ibm-granite/granite-4-nano , October 2025

Reference 49

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source=pdf_text observed=2026-08-04T07:50:50.699614Z digest=sha256:4d29930a88b88406cdd22758c983503c71408590fcb210e7b4905205caacb9d1

Observation 7ed09ea0-25af-4e5f-ba40-fbd752be22eb · outbound

This paper cites Codescout: An effective recipe for reinforcement learning of code search agents, 2026.

Antares: Foundation Models for Agentic Vulnerability Localization Codescout: An effective recipe for reinforcement learning of code search agents, 2026

Reference 50

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source=pdf_text observed=2026-08-04T07:50:50.702346Z digest=sha256:6c90d203e38dcb88a3121c2c4d50a770b6fd5d72b2687d71f0e71838ae4fafa9

Observation ab8a6b81-82a6-4b71-80af-d073073f17ba · outbound

This paper cites Glm-4.5: Agentic, reasoning, and coding (arc) foundation models,.

Antares: Foundation Models for Agentic Vulnerability Localization Glm-4.5: Agentic, reasoning, and coding (arc) foundation models,

Reference 51

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source=pdf_text observed=2026-08-04T07:50:50.704959Z digest=sha256:6b2dd105fec0a4d6dfcabdc582896cdcc059fd1b544aff0e61349b30524113ca

Observation 9edc7e00-e779-40c8-a131-fc45a1e6b474 · outbound

This paper cites GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models.

Antares: Foundation Models for Agentic Vulnerability Localization GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Reference 52

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source=pdf_text observed=2026-08-04T07:50:50.707676Z digest=sha256:22977fb6c25923a36f47dfd840325a4d8712165e10b1df8dc1e714ec27c05fef

Observation aafb62fd-1607-4c2c-8666-cc7626c2bdfa · outbound

This paper cites Think before you retrieve: Learning test-time adaptive search with small language models, 2025.

Antares: Foundation Models for Agentic Vulnerability Localization Think before you retrieve: Learning test-time adaptive search with small language models, 2025

Reference 53

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Observation 9eb5be75-d43a-4f3a-8154-0fba4ac67dfe · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Antares: Foundation Models for Agentic Vulnerability Localization Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 54

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source=pdf_text observed=2026-08-04T07:50:50.728980Z digest=sha256:c599ec39984ed84b7c0b55c9b750e1b00d2a34bfeaf33dd17840979b5e1d00ec

Observation 8fb23fd9-8e3d-4217-a80b-676fa3d36c44 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

Antares: Foundation Models for Agentic Vulnerability Localization Kimi K2: Open Agentic Intelligence

Reference 55

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source=pdf_text observed=2026-08-04T07:50:50.715619Z digest=sha256:1d1e06d276f9dabbac6ba0ecd755918a53059d67c3087827bdfb7b92f44f7c90

Observation a020135b-db72-4db7-938e-70e3b0e99822 · outbound

This paper cites Next-Latent Prediction Transformers Learn Compact World Models.

Antares: Foundation Models for Agentic Vulnerability Localization Next-Latent Prediction Transformers Learn Compact World Models

Reference 56

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source=pdf_text observed=2026-08-04T07:50:50.718294Z digest=sha256:2a6a33fb85112ec9c0dfc6a483c330a81ce67dd355ca17b73c7c234f4f698a57

Observation be15f59d-dea4-4721-b0e8-6502e4d82df6 · outbound

This paper cites Dubniczky, Ridhi Jain, and Lucas C.

Antares: Foundation Models for Agentic Vulnerability Localization Dubniczky, Ridhi Jain, and Lucas C

Reference 57

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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=2026-08-04T07:50:50.721174Z digest=sha256:5137f60ce6f452580704d2fc7b40f371b71186e1e02e844cbbb395e6c493c753

Observation 6adfa989-c902-4dac-bf8c-e2e2e0fc43c7 · outbound

This paper cites Qrs: A rule-synthesizing neuro-symbolic triad for autonomous vulnerability discovery, 2026.

Antares: Foundation Models for Agentic Vulnerability Localization Qrs: A rule-synthesizing neuro-symbolic triad for autonomous vulnerability discovery, 2026

Reference 58

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Observation 3dd60dc4-fa6f-46e7-8c5b-cc25238ae705 · outbound

This paper cites Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report.

Antares: Foundation Models for Agentic Vulnerability Localization Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

Reference 59

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source=pdf_text observed=2026-08-04T07:50:50.742631Z digest=sha256:c77e5cc49a0f964e26e29f0295c3105980b94996839514384656769540eb6c73

Observation baca496c-87ad-44f1-9007-d6536ec78bd1 · outbound

This paper cites From trace to line: Llm agent for real-world oss vulnerability localization, 2026.

Antares: Foundation Models for Agentic Vulnerability Localization From trace to line: Llm agent for real-world oss vulnerability localization, 2026

Reference 60

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source=pdf_text observed=2026-08-04T07:50:50.745633Z digest=sha256:4b0893ba23e7354a1e7eb3743afdc4924bcee6b0b33ada6c98d05266ec920652

Observation 096e9981-28da-4acb-b746-5666dfc6758b · outbound

This paper cites Reposvul: A 32 repository-level high-quality vulnerability dataset, 2024.

Antares: Foundation Models for Agentic Vulnerability Localization Reposvul: A 32 repository-level high-quality vulnerability dataset, 2024

Reference 61

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Observation 0b475920-b1fc-4e51-bad1-a633f5abc900 · outbound

This paper cites ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?.

Antares: Foundation Models for Agentic Vulnerability Localization ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?

Reference 62

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source=pdf_text observed=2026-08-04T07:50:50.734598Z digest=sha256:f276db416d52d0bee912d992f9a199eee7df66fdc9c3e8405639d11dd21f835f

Observation 62dfc1af-811a-49f6-9127-a9b2428a3f1c · outbound

This paper cites Cybergym: Evaluating ai agents’ real-world cybersecurity capabilities at scale, 2026.

Antares: Foundation Models for Agentic Vulnerability Localization Cybergym: Evaluating ai agents’ real-world cybersecurity capabilities at scale, 2026

Reference 63

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source=pdf_text observed=2026-08-04T07:50:50.737498Z digest=sha256:46296b6526283c6db69f8869f6da8a50b3b601d9e8e1a8368c28cbeb614e1c89

Observation a1a3bd8f-2f34-42bd-9b4a-cc5cf0025592 · outbound

This paper cites Vulagent: Hypothesis-validation based multi- agent vulnerability detection, 2025.

Antares: Foundation Models for Agentic Vulnerability Localization Vulagent: Hypothesis-validation based multi- agent vulnerability detection, 2025

Reference 64

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Observation 6ce1daa3-2ba2-4f10-aa47-dc8944165bff · outbound

This paper cites Fastcontext: Training efficient repository explorer for coding agents,.

Antares: Foundation Models for Agentic Vulnerability Localization Fastcontext: Training efficient repository explorer for coding agents,

Reference 65

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source=pdf_text observed=2026-08-04T07:50:50.762166Z digest=sha256:961b8a89286ad4f491501fb67a1b3edd3d213f2e72f4dedd42f99b2fca3b7c0a

Observation 1b781047-1e25-477c-a302-f683c550c201 · outbound

This paper cites Deepresearcher: Scaling deep research via reinforcement learning in real-world environments,.

Antares: Foundation Models for Agentic Vulnerability Localization Deepresearcher: Scaling deep research via reinforcement learning in real-world environments,

Reference 66

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source=pdf_text observed=2026-08-04T07:50:50.767938Z digest=sha256:6e95dc6f62633af71f9347ce9b0f1be545b5f6e03be6de2ef987330eec9b11a0

Observation 40c92d40-750d-4fce-a9ae-132745f5ef9a · outbound

This paper cites Qwen3 Technical Report.

Antares: Foundation Models for Agentic Vulnerability Localization Qwen3 Technical Report

Reference 67

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source=pdf_text observed=2026-08-04T07:50:50.748230Z digest=sha256:4a9de70257b184b769b05a1f8228f6a81762e7b06817b52753c2a0569dba6f2d

Observation a2ae8485-8577-4c17-9530-1fe5e60b754c · outbound

This paper cites Llama-3.1-foundationai-securityllm-reasoning-8b technical report,.

Antares: Foundation Models for Agentic Vulnerability Localization Llama-3.1-foundationai-securityllm-reasoning-8b technical report,

Reference 68

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source=pdf_text observed=2026-08-04T07:50:50.750869Z digest=sha256:98a6a1741f1772f74044cc53d253dbbacf8cd67f06863e4a42df15595fd00cf3

Observation 21a84032-92f3-4f53-9f95-c7f06280893c · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 69

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source=pdf_text observed=2026-08-04T07:50:50.753666Z digest=sha256:a98eda07b9925206df16ee7d3c28d73fa8ddd7f0dbdc26b4d07a8776ead70257

Observation 5a6c57b7-ac77-4224-8f20-dda223e138ef · outbound

This paper cites $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains.

Antares: Foundation Models for Agentic Vulnerability Localization $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 70

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Observation 2a4c1f3a-97d8-4f75-b64b-56aac6cc9689 · outbound

This paper cites Primus: A pioneering collection of open-source datasets for cybersecurity llm training, 2025.

Antares: Foundation Models for Agentic Vulnerability Localization Primus: A pioneering collection of open-source datasets for cybersecurity llm training, 2025

Reference 71

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source=pdf_text observed=2026-08-04T07:50:50.759292Z digest=sha256:3a11e73df3830be9765dfb76c4de5fbc0802347e941ed3e3cf7c4b0fc1d0278c

Observation dd85e96e-4af4-45fd-96f2-f1463e531ae2 · outbound

This paper cites FastContext: Training Efficient Repository Explorer for Coding Agents.

Antares: Foundation Models for Agentic Vulnerability Localization FastContext: Training Efficient Repository Explorer for Coding Agents

Reference 73

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source=pdf_text observed=2026-08-04T07:50:50.764807Z digest=sha256:1a33849d8a6dc42b50ec56d82a94cbe51386b39da5ff1a344b34d0c930fc64eb

Observation 37badcf7-0561-48c2-ae28-9dacf9426ed0 · outbound

This paper cites DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments.

Antares: Foundation Models for Agentic Vulnerability Localization DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments

Reference 75

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source=pdf_text observed=2026-08-04T07:50:50.770562Z digest=sha256:eb54f82c33189d098667aa4b950cac795fd98321f4d5f094903611c42c6e0657

Observation 4c08ddd2-4eca-44c5-a448-b96aef928c2e · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 76

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source=pdf_text observed=2026-08-04T07:50:50.774391Z digest=sha256:25fc00c159d2e36bd3d37a5aa634f7daf251e609e9d42cdb3d40cf9f22bda6f8

Observation f6ce17ae-2218-4f99-a8de-7f27cbaac0d2 · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 77

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source=pdf_text observed=2026-08-04T07:50:50.777125Z digest=sha256:fd68aa2666dd6c81f57e740fe58dc867c320736e7bdda4ffe2adeccf52325f9f

Observation 124e6b7c-b9d0-48ac-a588-1ad6f7da51f1 · outbound

This paper cites The model checkpoint, inference parameters, tool definitions, sandbox, scoring function, and evalu- ation entries remain unchanged.

Antares: Foundation Models for Agentic Vulnerability Localization The model checkpoint, inference parameters, tool definitions, sandbox, scoring function, and evalu- ation entries remain unchanged

Reference 78

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source=pdf_text observed=2026-08-04T07:50:50.779900Z digest=sha256:41afee7191f7d5bfe2ec2ee5a8c4940882d93b16ff87ca84c11450b614c36887

Observation 21fd2a86-5fdf-4954-8add-2432709e1d40 · outbound

This paper cites RaDeR: Reasoning-aware Dense Retrieval Models.

Antares: Foundation Models for Agentic Vulnerability Localization RaDeR: Reasoning-aware Dense Retrieval Models

Reference 2025

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unresolved
no resolver link, observed 2026-08-04T07:50:50.587651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:50:50.587651Z digest=sha256:86bdce79fca70baf67c6eb3b1f875ddf8cf6ef4f0883ec179f9927bf28c0714b

Observation 39b4dd46-1ce9-4a3d-899b-02831b1436c7 · outbound

This paper cites an unresolved cited work.

Antares: Foundation Models for Agentic Vulnerability Localization Unresolved cited work

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-04T07:50:50.713092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:50:50.713092Z digest=sha256:186a3c3edf44defb7b86c2e379fcf5f63b36dce2c887866312386240b83fbb7a

Pith citing papers

No inbound Pith citation observations are available.