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Notes on evaluation
165 notes, page 1 of 7
Attention Sees, MLP Refuses: Tracing the Attention-to-MLP Safety Pathway in LLMs
Across 18 base-instruct model pairs spanning Qwen, Llama, and Gemma, the authors report that harmfulness is more readily decoded from attention updates while MLP updates contribute more strongly to harm-selective…
DRYLAB-Bench: Benchmarking the Biosecurity Risk of Agentic LLM Mutation Design
DRYLAB-Bench evaluates agentic mutation-design capability in 30 hazardous scenarios distilled from biosecurity guidelines, using multi-round tool-augmented interactions. It scores designs against 187,695 empirical…
A Privileged Teacher That Only Scores Cannot Search: Critique-Conditioned On-Policy Self-Distillation for Reasoning
The study tests whether scoring signals in on-policy self-distillation localize errors and push probability away from erroneous student tokens. It reports that full-distribution KL and token log-ratio signals do…
RATED: Reliability-Aware AI Agent Tool Retrieval via Execution Dynamics
RATED combines a frozen dual encoder for semantic matching with a lightweight contextual-bandit module that reranks tools using real-time execution feedback. The authors introduce EcoAgent, a benchmark of 5,172 tools…
X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems
X-AgentRed constructs a directed graph of tool dependencies, effects, harms, and execution preconditions to discover harmful cross-service action paths. Execution feedback expands and refines the paths through tool…
BrickBench: Evaluating Agentic Brick Design
The preprint introduces BrickBench, a benchmark for text-conditioned LEGO-set design. Agents must produce assemblies that satisfy semantic and design criteria while remaining physically buildable, selecting parts from…
Accurate but Not Humble: Evaluating Epistemic Humility in LLM Agents under Knowledge Conflict
The preprint evaluates epistemic humility through three trajectory-level behaviors: Identify, Solve, and Escalate. It tests controlled and naturally occurring conflicts between parametric knowledge and retrieved…
OnTrack: Real-Time Monitoring and Intervention in LLM Agent Trajectories via Streaming Structure-Aware Optimal Transport
The preprint proposes OnTrack, a streaming monitoring mechanism that compares an agent's steps and dependencies against recorded successful runs to alert users or block the agent. It evaluates full-reference…
When Should Agents Think? Adaptive Reasoning via Cross-Turn Estimation
The preprint proposes Reasoning Adaptation through Cross-Turn Estimation (RACE), which estimates when prior reasoning remains sufficient for subsequent actions. Its LoGiC procedure identifies reasoning turns whose…
Ecology of AI Agents: Collaboration Creates a Population Threshold for Takeoff
The preprint develops a population-level model in which agent fitness depends on cybersecurity capability. It reports that without collaboration, takeoff requires individual capability above a critical threshold; with…
GeoReform: Reflective Formalization Evolution for Multimodal Geometry Problem Solving
The preprint proposes GeoReform, which treats geometric formalization as an optimizable policy rather than a fixed parser output. It collects failed rollouts, diagnoses representation defects, and mutates how entities…
Searching for "Harmful Refusal": A Psychometric Audit of an AI Safety Benchmark
The preprint audits whether harmful refusal is a single measurable attribute in HELM Safety. It reports saturation in three candidate datasets and uses multidimensional item-response theory plus differential item…
Cited but Not Consulted: A Counterfactual Audit of Legal Chain-of-Thought Faithfulness
The preprint tests whether legal models' named statutes or precedents causally support their verdicts. Holding case facts fixed, it substitutes the named authority and examines verdict changes and hidden-state dynamics…
On the estimation and validity of AI time horizons---a statistical look at the METR plot
The preprint recomputes METR-style 50% AI time horizons over 228 tasks and 26 AIs using splines and item-response theory. The authors report that the fitted spline is nearly flat from roughly 2–30 minutes and close to…
EvoAlloc: A Self-Evolving Resource Allocation Agent for Efficient Program Evolution
EvoAlloc is described as a self-evolving resource-allocation agent for LLM-based program evolution. It consolidates prior search and allocation outcomes into reusable experience, revises its allocation strategy, and…
HRIL: Learning Multimodal Synergy via Higher-Order Tensor Modeling
The preprint frames multimodal synergy as higher-order dependence that can be lost by pairwise fusion. HRIL uses an empirical cross-moment tensor with Tucker decomposition and a synergy-aware regularizer. The authors…
Recursive Self-Improvement through Multi-Agent Self-Supervision
The work describes MASS, which alternates evolutionary workflow optimization with supervised fine-tuning on self-generated trajectories. The abstract reports discovery of multi-agent workflows and, over two cycles with…
Prior or Feedback? What an LLM Uses When Adapting Neural Operators
The study tests whether an LLM scientific agent adapts neural-operator tuning using experimental feedback under a limited trial budget. The authors report lower held-out nRMSE than random search and Bayesian…
Verdict Without the Rule: Diagnosing and Auditing Regulatory Rule Sensitivity in LLM Compliance Systems
The preprint tests regulatory-rule sensitivity by deleting, swapping, or negating a rule while holding the case fixed across five models and 20 domains. It reports that verdicts are often invariant to large rule…
ScienceClaw: Benchmarking Continual Self-Evolution of AI-for-Science Agents Across the Natural and Social Sciences
The preprint formalizes fixed-parameter program self-evolution that links task solving, scientific verification, and program updates. ScienceClaw-Eval spans 23 disciplines and measures correctness, evolutionary gain…
Sherpa: Teaching LLMs to Teach Adaptively
The preprint introduces Sherpa, a multi-turn reinforcement-learning framework that trains an LLM teacher against multiple student archetypes with distinct learning preferences. The teacher is optimized directly against…
Transect: Retaining Observability for Long-Horizon LLM Agent Evaluations
The preprint presents Transect, an open-source package built on Inspect Scout for analyzing long agent runs whose transcripts can span hundreds of pages. Configurable evaluation families align recorded events, token…
VeriFine: Scaling Verification for Self-Improvement in Embodied Reasoning
The preprint proposes an agent harness that co-evolves the policy, training curriculum, and judge. A Policy Improvement Loop diagnoses recurring failures and builds an adaptive curriculum; when verification becomes a…
Agent in a Bottle: Can LLM Agents Turn Their Capabilities Into Cheap, Scalable Artifacts?
The preprint introduces BOTTLED, a benchmark in which agents receive an unlabelled workload and must complete it under fixed time, compute, and LLM API budgets. Agents may train a small model or write a reusable…
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