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2,343 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.
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Notes on evaluation
165 notes, page 2 of 7
MedZERO: Self-Evolving Agents for Open-Ended Medical Reasoning Through Controlled Knowledge Accumulation
The preprint presents MedZERO, a self-evolving framework for open-ended medical reasoning. An Examiner generates medical question-option pairs, while a Reasoner solves them with evidence-grounded multi-turn reasoning…
ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding
The preprint introduces a benchmark for unified evaluation of risk-treatment capabilities in coding agents. It maps Avoidance, Transfer, Mitigation, and Acceptance from software risk management to 200…
SquidAgent: Parallelize Wisely, Coordinate Efficiently
The preprint identifies re-exploration and alignment as hidden costs that can make parallel multi-agent systems slower than a single-agent baseline. It proposes a token-based decision criterion, direct forking from the…
WorldSolver: Can LLM Agents Simulate the Physical Dynamics via Solver Generation?
The preprint introduces WorldSolver, a benchmark of 168 simulation tasks derived from physical phenomena in 61 classic computer-graphics papers across seven physical domains. Each task provides a code scaffold while…
AgentPrivArena: Evaluating and Auditing Real-world AI Agent Privacy
The preprint introduces AgentPrivArena, a reproducible environment that integrates authentic MCP tools and self-hosted services to evaluate privacy risks during realistic multi-step agent execution. It proposes…
What Did the Agent Actually Do? Evidence-Grounded Oversight for Long-Horizon Agents
The preprint introduces AgentMonBench, a software-engineering benchmark for judging requirement/behavior alignment and identifying consequential autonomous decisions that warrant verification. Its Evidence-Grounded…
HERA: Harness-Environment Co-Evolution for Reliable Agentic Abstention
The preprint introduces HERA, a framework that constructs verifiable feasible/infeasible task pairs through controlled environment mutations and adapts the agent harness toward prior weaknesses. The abstract reports…
ImproveAnyTask: An Autonomous Post-Training Harness for Iterative Model Self-Improvement
The preprint describes an autonomous post-training harness that attributes errors, selects update directions, and executes model updates under a limited compute budget. It combines metric- and case-level analysis…
HazardWeaver: Scientific Route Selection for Hazard Analysis Agents
The preprint formulates hazard-analysis automation as state-dependent scientific route selection. HazardWeaver combines an evidence-linked Hazard Knowledge Compiler with a Hazard Capability Graph that checks…
HyperBrowseComp: A Multilingual and Multimodal Stress Test for Web-Browsing Agents
The preprint presents 423 manually authored and human-validated questions across 13 languages. Items require obscure evidence discovery, multi-step clue chains, and heterogeneous sources such as videos, scanned…
Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis
The preprint introduces task-harness co-evolution for recursive reasoning-data synthesis. Online self-improvement turns solver failures into reusable skills, while post-task updates revise skills, prompts, and…
Agents Are Systems, Not Models: Rethinking Agentic Evaluation
The preprint evaluates agents as configurable systems whose task information, reasoning settings, self-verification, time budget, and backbone model all affect outcomes. On four scientific tasks, the abstract reports…
Causal Memory Policy: Making Memory Utility Identifiable by Intervening on Retrieval
The preprint identifies a retrieval-level positivity problem: memories that are never retrieved cannot have their utility identified by store-level interventions. It proposes Causal Memory Policy, which reserves…
Mingbird: A Local-First Agent Harness Enabling Small Open Models to Complete Real Tasks
The preprint argues that many failures of 2B–9B open models on real tasks arise from the harness rather than the model. Mingbird is a local-first harness for Windows and Ollama with mechanisms including a byte-level…
VISTA: A Visual Harness for Reasoning in an Interactive World
The technical report introduces a visual harness that gives a multimodal model long-horizon visual context through direct perception, lossless visual memory, active retrieval, and input reorganization. The abstract…
The AI Assessment Sandbox Configurator: A Framework to Support Technical Assessment in AI Regulatory Sandboxes
The preprint describes an open-source framework for technical testing in AI regulatory sandboxes, motivated by EU AI Act obligations. It proposes a plug-in test and control catalogue, a shared data model for…
External Observers May See More Clearly: Cross-Model Span-Level Hallucination Detection in Large Language Models via Hidden State Probing
The preprint presents a hidden-state method for identifying the onset and continuation of hallucinated spans rather than making only token-level binary judgments. It proposes an external observer model that probes the…
OpenMTB-Audit: Exposing Over-Refusal and Clinical Expert Perspectives in LLM-Based Molecular Tumor Board Safety Evaluation
The preprint introduces a benchmark of 500 synthetic non-small-cell lung-cancer cases with four safety labels, including Supported, Partially Supported, Unsupported, and Insufficient Information. Across eight model…
Turbo Harness: Instance-Adaptive Harness Optimization
The preprint introduces Turbo Harness, which reuses artifacts from a completed global harness-optimization run, summarizes them into a structured playbook, and trains a harness editor to generate instance-specific…
WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents
The preprint presents 213 anomaly tasks across 13 Unreal Engine 5 and three.js environments, covering five anomaly families. It evaluates five frontier models under a fixed exploration budget using VLA-led exploration…
You Cannot Pick a Provider From the Price List: Market-Aware Routing for Open-Weight LLM Inference
The preprint argues that open-weight inference routing must choose both a model and the provider serving it. Across live endpoints, models, task types, and three measurement waves, it reports that the same model can…
Do LLM Agents Execute the Plans They Declare? From Planning-Mode Declaration to Pattern-Specific Execution
The preprint defines a Plan Declaration–Execution Gap and evaluates four declared planning modes: Predefined, Sequential, Hierarchical, and Search. Across four benchmarks and three LLMs, the abstract reports that only…
Failure-Transparent Agents: Benchmarking Post-Failure Reporting in Tool-Using Language Models
The preprint introduces a controlled benchmark for cases where a required tool fails and an agent may report success without supporting evidence. The benchmark contains 100 tasks with deterministic failure traces…
Game Arena: Strategic LLM Evaluation in Competitive Environments
The technical report describes Kaggle Game Arena, an open platform for head-to-head LLM evaluation in structured competitive environments. It covers pilot environments for chess, poker, and Werewolf, spanning perfect…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
