Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents | Paper Citation Record

Observation dd50a0ba-0227-47cf-b045-7c1c0072b35d · outbound

This paper cites Claude code, 2024.https://claude.com/claude-code.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Claude code, 2024.https://claude.com/claude-code

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.920647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7557ce4c-1c0b-48be-a577-805828f92a99 · outbound

This paper cites Models overview.https://platform.claude.com/docs/claude/docs/models-overview, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Models overview.https://platform.claude.com/docs/claude/docs/models-overview, 2026

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.906832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 560ffd42-11fb-40ea-b414-76b7949bbc90 · outbound

This paper cites Building effective agents.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Building effective agents

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.892417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f2924955-bd89-4804-b29b-550ed3a30566 · outbound

This paper cites $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.865427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73fe18b2-1629-4890-a28d-c9f2fc1df10e · outbound

This paper cites MLE-bench: Evaluating machine learning agents on machine learning engineering.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents MLE-bench: Evaluating machine learning agents on machine learning engineering

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.878606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e4edd941-19be-441f-87f2-4f4d0ff8f748 · outbound

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

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.874574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6047447-9ca6-4feb-8f1d-075c78ce9727 · outbound

This paper cites Datasheets for datasets.Communications of the ACM, 64(12):86–92, 2021.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Datasheets for datasets.Communications of the ACM, 64(12):86–92, 2021

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.879593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b2aadf6-456c-45d5-9404-a5c67300fee5 · outbound

This paper cites Gemini 3.1 Pro: Model card.https://deepmind.google/models/model-cards/ gemini-3-1-pro/, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Gemini 3.1 Pro: Model card.https://deepmind.google/models/model-cards/ gemini-3-1-pro/, 2026

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.856111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 94310d55-504c-4172-8c4c-91f3f2f8d770 · outbound

This paper cites Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.887791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d262a897-5a56-4027-8122-d9875218a7ec · outbound

This paper cites ProcCtrlBench: Evaluating Process-Level Defects and Control Preservation in LLM Coding Agents.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents ProcCtrlBench: Evaluating Process-Level Defects and Control Preservation in LLM Coding Agents

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.892302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ec3ce90-7e45-4177-ba2f-09dbbbe802f9 · outbound

This paper cites Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.896736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32704800-6895-4df4-93cc-8bb392eb205f · outbound

This paper cites MLAgentBench: Evaluating language agents on machine learning experimentation.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents MLAgentBench: Evaluating language agents on machine learning experimentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.843216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f2da929-ae61-4916-8c45-5c4111efbbbe · outbound

This paper cites FollowBench: A multi-level fine-grained constraints following benchmark for large language models.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents FollowBench: A multi-level fine-grained constraints following benchmark for large language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.829881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b06da15-8e42-4bf1-8756-504e09057943 · outbound

This paper cites Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.816783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 28198d65-8b6a-4848-b2d1-a9e0f1108062 · outbound

This paper cites AgentBench: Evaluating LLMs as agents.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents AgentBench: Evaluating LLMs as agents

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.803265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation df2458e0-0b6a-4ac4-9ef9-0fa7cf30241d · outbound

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

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.917646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efb42d1a-3422-4ce0-9941-37f27846325d · outbound

This paper cites GAIA: A benchmark for general AI assistants.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents GAIA: A benchmark for general AI assistants

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.789693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d3118d91-10d5-4cf4-b83f-706f44eddd52 · outbound

This paper cites MiniMax M2.7: Model self-improvement.https://www.minimax.io/models/text/m27, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents MiniMax M2.7: Model self-improvement.https://www.minimax.io/models/text/m27, 2026

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.775883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e054397b-6d58-42a5-8ac3-d116d6fe3abc · outbound

This paper cites Kimi K2.6 model card.https://huggingface.co/moonshotai/Kimi-K2.6, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Kimi K2.6 model card.https://huggingface.co/moonshotai/Kimi-K2.6, 2026

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.762751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5ae1cba8-2279-44c7-b66a-0cd602440146 · outbound

This paper cites GPT-5.5 model.https://developers.openai.com/api/docs/models/gpt-5.5/, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents GPT-5.5 model.https://developers.openai.com/api/docs/models/gpt-5.5/, 2026

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.749856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7a44892d-486a-4291-9b8c-752d88af48bd · outbound

This paper cites Introducing SWE-bench verified.https://openai.com/index/ introducing-swe-bench-verified/, 2024.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Introducing SWE-bench verified.https://openai.com/index/ introducing-swe-bench-verified/, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.736649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff6098a0-7b02-4743-a8fd-44d32f79c60b · outbound

This paper cites Patil, Tianjun Zhang, Xin Wang, and Joseph E.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Patil, Tianjun Zhang, Xin Wang, and Joseph E

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.722887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 767cbce2-2a76-4483-a3df-ecf87742d934 · outbound

This paper cites Patil, Huanzhi Mao, Fanjia Yan, Charlie Ji, Vivek Suresh, Ion Stoica, and Joseph E.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Patil, Huanzhi Mao, Fanjia Yan, Charlie Ji, Vivek Suresh, Ion Stoica, and Joseph E

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.709443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7ed8de2-7101-4010-ad4c-8a6e5f775006 · outbound

This paper cites Generalizing verifiable instruction following.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Generalizing verifiable instruction following

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.696155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 45da52c9-23f5-44ad-961a-597793a83213 · outbound

This paper cites AgentIF: Bench- marking instruction following of large language models in agentic scenarios.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents AgentIF: Bench- marking instruction following of large language models in agentic scenarios

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.682836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 87e0b0e3-8571-4ad4-9c60-ec7efb7e25f3 · outbound

This paper cites InFoBench: Evaluating Instruction Following Ability in Large Language Models.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents InFoBench: Evaluating Instruction Following Ability in Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.959112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d094cc47-8480-4ff5-8985-7aeb92da1199 · outbound

This paper cites Qwen3.6-Max-Preview released.https://qwen.ai/blog?id=qwen3.6-max-preview, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Qwen3.6-Max-Preview released.https://qwen.ai/blog?id=qwen3.6-max-preview, 2026

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.669629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dbbf2186-5bb2-4760-95e3-1dfd29bb93e2 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Toolformer: Language models can teach themselves to use tools

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.655948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 35d5b2e3-80c5-44ac-9dc9-57b4ad1685d0 · outbound

This paper cites Seed2.0 model card.https://yfz.ai/Seed2.0_Model_Card.pdf, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Seed2.0 model card.https://yfz.ai/Seed2.0_Model_Card.pdf, 2026

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.642324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 90050bbd-78d8-4c3a-828c-624629e18d88 · outbound

This paper cites OpenAI GPT-5 System Card.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents OpenAI GPT-5 System Card

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.975569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82bd7606-6097-4408-aa42-c0d2a839f38e · outbound

This paper cites PaperBench: Evaluating AI's Ability to Replicate AI Research.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents PaperBench: Evaluating AI's Ability to Replicate AI Research

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.979863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a86962c-805c-4b22-bedf-f6a827ea6503 · outbound

This paper cites Step 3.5 Flash: Open frontier-level intelligence with 11b active parameters.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Step 3.5 Flash: Open frontier-level intelligence with 11b active parameters

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.984189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64808c17-4970-4704-b91e-663890d60418 · outbound

This paper cites Tencent unveils Hy3 preview.https://www.tencent.com/en-us/articles/2202320.html, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Tencent unveils Hy3 preview.https://www.tencent.com/en-us/articles/2202320.html, 2026

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.988276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77423fd4-60a9-4daf-8854-e3c86d5d6246 · outbound

This paper cites AppWorld: A controllable world of apps and people for benchmarking interactive coding agents.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents AppWorld: A controllable world of apps and people for benchmarking interactive coding agents

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.629240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2e12bf06-e39b-43d8-8e1e-5e0da8119158 · outbound

This paper cites The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:52.996449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee682b72-a39b-4e0c-9b19-2a99d4a285e7 · outbound

This paper cites CodeIF-Bench: Evaluat- ing instruction-following capabilities of large language models in interactive code generation.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents CodeIF-Bench: Evaluat- ing instruction-following capabilities of large language models in interactive code generation

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.001057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45288d20-abf6-4f03-a50f-de7b520a4308 · outbound

This paper cites Benchmarking complex instruction- following with multiple constraints composition.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Benchmarking complex instruction- following with multiple constraints composition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.615614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aae303cf-a1b7-4cc0-bbe1-371988a61791 · outbound

This paper cites LIFBench: Evaluating the instruction following performance and stability of large language models in long- context scenarios.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents LIFBench: Evaluating the instruction following performance and stability of large language models in long- context scenarios

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.602044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 037af9e7-2a24-4442-a52b-9270db7beb63 · outbound

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

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.013801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87759daf-12d3-4382-96a8-f99e0c5820a9 · outbound

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

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.018025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6592ac29-096c-42b7-8f8a-2e77a9c3a174 · outbound

This paper cites Jimenez, Alex L.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Jimenez, Alex L

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.587390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7b207577-7c42-4392-ac3c-2ae67eeabfd9 · outbound

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

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.026282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fca0b68c-e694-4d6d-a48d-84bda6132c8f · outbound

This paper cites OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.030478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccd56daf-e901-4d80-a080-3f9f47707b8f · outbound

This paper cites GLM-5.1 release notes.https://docs.z.ai/release-notes/new-released, 2026.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents GLM-5.1 release notes.https://docs.z.ai/release-notes/new-released, 2026

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.572368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fa3a73aa-147a-4fc1-b001-5baadf511a37 · outbound

This paper cites CFBench: A comprehensive constraints- following benchmark for LLMs.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents CFBench: A comprehensive constraints- following benchmark for LLMs

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.558499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 44cd9b76-4a7b-4d10-8b90-bf3e3b219e0c · outbound

This paper cites IHEval: Evaluating language models on following the instruction hierarchy.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents IHEval: Evaluating language models on following the instruction hierarchy

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.545016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 422a8ed1-6684-4f66-b8f2-120899eaada8 · outbound

This paper cites SpecBench: Measuring Reward Hacking in Long-Horizon Coding Agents.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents SpecBench: Measuring Reward Hacking in Long-Horizon Coding Agents

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.049011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53a884e0-5fd7-4236-8f10-b025d740cf6a · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Instruction-Following Evaluation for Large Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:53.053616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34ebd60a-8d73-4711-ba6a-41722ec77425 · outbound

This paper cites Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, and Graham Neubig.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, and Graham Neubig

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:35:53.531867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0c81da32-8ed6-4150-904c-04ab39407e5a · outbound

This paper cites Keep generated summaries compact,.

Harness-IF: Evaluating Instruction Following Across Instruction Surfaces in Coding Agents Keep generated summaries compact,

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