TrustMI: Causally controlling how assistants trust their users
cs.CL
Submitted: 2026-10-05
Updated: 2026-10-05
Code: https://github.com/UKGovernmentBEIS/inspect_ai
Sources
- $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
- The Llama 3 Herd of Models
- Agentic Misalignment: How LLMs Could Be Insider Threats
- Reliability without Validity: A Systematic, Large-Scale Evaluation of LLM-as-a-Judge Models Across Agreement, Consistency, and Bias
- LLM Evaluators Recognize and Favor Their Own Generations
- GPQA: A Graduate-Level Google-Proof Q&A Benchmark
- Olmo 3
- AgentJudgeBench: A Multi-Difficulty Benchmark for Evaluating LLM Judges on Agentic Tool-Calling
- Representation Engineering: A Top-Down Approach to AI Transparency
Related papers
- Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
- Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
- Subliminal Steering: Stronger Encoding of Hidden Signals
- MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
- The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
- Untangling the Mechanisms of Misleading Context in Medical Question Answering