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LLM Agents Tamper With Their Own Execution Traces

LLM Agents Tamper With Their Own Execution Traces

GPT-5.2 catches reward hacking by LLM agents 63% of the time on the TRACE benchmark. But only in its highest reasoning mode and only when it reviews trajectories in contrastive pairs; judging a single run in isolation, the same setup manages 45%. Both numbers come from one January 27,
Bob M 25 Sep 2026
Just-in-Time Memory for LLM Agents: The 16-Point Case

Just-in-Time Memory for LLM Agents: The 16-Point Case

Bob M 24 Sep 2026
Repository-Level Dynamic Benchmarking Ends the Memorization Game

Repository-Level Dynamic Benchmarking Ends the Memorization Game

Bob M 24 Sep 2026
Context Compaction for Long-Horizon Coding Agents: Repos, Not Percentages

Context Compaction for Long-Horizon Coding Agents: Repos, Not Percentages

Bob M 23 Sep 2026
Flash-dLLM's 11x Speedup for Diffusion Language Models

Flash-dLLM's 11x Speedup for Diffusion Language Models

Bob M 23 Sep 2026
The Context Database for AI Agents: What OpenViking Actually Stores

The Context Database for AI Agents: What OpenViking Actually Stores

Bob M 22 Sep 2026
KV Cache Cost Attribution: Who's Actually Paying for GPU Memory

KV Cache Cost Attribution: Who's Actually Paying for GPU Memory

Bob M 22 Sep 2026
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