Field notes
2,343 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.
Click the web, then scroll to zoom
Every note is in the list below. The web of topics draws here once the page has loaded.
2,343 notes and 295 topics.
- Question answered
- Source note
- Topic
- Shared notes
All notes, newest first
2,343 notes, page 3 of 98
Mimir: Physics-Grounded LLM Agents for Long-Horizon Irrigation Control
The preprint studies long-running irrigation decisions where actions change future states and errors compound. Mimir combines a structured physical interface, deterministic simulation, verified revision, bounded action…
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…
Agent Error Dataset: Scaling 50,000 Error--Diagnosis Pairs for Failure Analysis and Error-Aware Post-Training
The preprint introduces 50,228 error-diagnosis pairs from 9,961 tasks across 33 environments, 19 harness families, and 23 policy models. Its Agentic Error-to-Training pipeline preserves traces and execution metadata…
Cogentic: Multi-Agent Orchestration for Automated Proof Discovery
The preprint describes an orchestrator that assigns independent provers to competing proof directions, uses specialized adversarial verification components, and promotes confirmed intermediate results into a persistent…
PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn Agents
The technical report studies pivotal mistakes that move an agent farther from task completion during multi-turn interaction. Across three Qwen3 models, the abstract reports that more than half of failed rollouts…
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…
HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment
The preprint uses hidden states before generation and at the end of an answer to predict correctness for local-model deployment. HARISSA fine-tunes both states and uses a single policy to choose among increasingly…
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…
Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning
The preprint introduces an inference-time harness in which a controller explicitly decides what partial work to reuse, whether to restart, when to stop, and which next work to dispatch. Workers perform task-level…
Learning Meta-Skills for Agent Harness Design in Test-Time AI4AI
The preprint studies a Builder model that learns to construct better execution environments for a frozen Target model. Its Meta-Skill encodes when support is needed and what resources to provide; the Builder learns…
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…
Reinforcing Agentic Creativity in Scientific Ideation with Night Science
The preprint introduces AI Night-Scientist, an agentic framework that uses reinforcement learning to shape when and how a model departs from predictable reasoning. It models creativity along action, process, and…
Report: Progressive Disclosure of Agent Skills
The report describes a Workday deployment context in which named procedures, or skills, are added to an LLM agent's context. It evaluates progressive disclosure (lazy-loading) of skills as a way to control the cost of…
Shockingly Simple Self-retrospection Improves Agentic Models Without RL
The preprint introduces Retrospection-Only Fine-Tuning (ROFT), an online procedure in which an agent attempts a task, observes feedback, generates a retrospective explanation, and fine-tunes only on the explanation…
Share-Borne AI Virus: Memory-Hopping Attacks Across LLM Agents
The preprint describes artifact-mediated propagation, in which adversarial content inserted into a shared artifact is stored in one assistant's persistent memory, reproduced in a later artifact, and acquired by another…
Up and Down the Abstraction Ladder: Code-Based Skills for Language Agents
The preprint studies reusable code-based skills for agents that otherwise must repeatedly choose low-level actions. In NetHack, the authors compare primitive actions, semantic skills, and combinations of both across…
Learning to Stop without Learning to Stop: Self-Supervised Confidence Training Improves Reasoning Efficiency
The preprint studies whether reasoning efficiency can improve without directly optimizing length or adding an inference-time stopping mechanism. It fine-tunes models to predict confidence at intermediate points in…
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…
Multi-agent Scaling Across Disjunctive and Compensatory Tasks
The preprint introduces a taxonomy of group tasks and analyzes multi-agent LLM scaling on disjunctive and compensatory tasks. Across 13 open-weight models and teams of up to 30 agents, the abstract reports that…
Mutable Transcripts: Mitigating Context Pollution through Editable Conversation State
The preprint proposes allowing users to revise prior conversation turns through natural-language edit requests, treating the transcript as an editable representation of conversational state rather than an immutable…
AD-WM: Action-Discriminative World Models for Counterfactual Model Predictive Control
AD-WM is a joint-embedding world model designed for counterfactual model predictive control. It combines residual latent dynamics with action-recovery regularization so the model preserves action-dependent differences…
How does Adversarial Influence Scale in Multi-Agent Systems?
The preprint studies deception in multi-agent deliberation. Its abstract reports that susceptibility depends on the proportion of deceivers rather than total group size, that defection rises approximately linearly with…
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.
