LongHarness Bench: Stress-Testing Language Model Harnesses for Long-Context Reasoning

arXiv:2609.38137 · cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/gkamradt/needle-in-a-haystack

Project page: https://stringnlplab.github.io/longharness/ABSTRACT

Terminology

• Accuracy — 71× in this paper · explained in 1 episode
• Benchmark — 32× in this paper · explained in 2 episodes
• Trace — 8× in this paper · explained in 2 episodes
• Verification — 8× in this paper · explained in 2 episodes
• Benchmarking — 5× in this paper · explained in 3 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Adaptive Reasoning — 3× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Agentic Coding — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks
• Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities
• Coding Agents are Effective Long-Context Processors
• MemoHarness: Agent Harnesses That Learn from Experience
• MemGPT: Towards LLMs as Operating Systems
• BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents
• GLM-5: from Vibe Coding to Agentic Engineering
• Recursive Language Models

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