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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 ai
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ComBodied Agents: a New Paradigm of Human-Centric Agentic AI
The text discusses a new paradigm called ComBodied Agents, which aims to bridge the gap between digital and embodied artificial intelligence by focusing on modeling, predicting, and supporting individual humans over…
ComBodied Agents: a New Paradigm of Human-Centric Agentic AI
The text introduces a new paradigm called ComBodied Agents, which aims to bridge the gap between digital and embodied agents in AI by focusing on understanding and supporting individual human state trajectories over…
ConVAWG: A Retrieval-Grounded Framework for Controlled Synthetic Dialogue Generation in Violence Against Women and Girls
The study presents ConVAWG, a framework that generates synthetic dialogues about Violence Against Women and Girls (VAWG) using a retrieval-based approach. The framework constructs scenarios based on persona seeds…
DuplexWorld: Can voice agents help you get through the day?
A research paper titled 'DuplexWorld' discusses the use of speech-to-speech (S2S) voice agents in various sectors like banking, insurance, travel, healthcare, logistics, and pathfinding. The study evaluates the…
GitSkills: A Dataset of Agent Skills on GitHub
The paper introduces GitSkills, a dataset of 3,797,117 SKILL.md files collected from public GitHub repositories in July 2026. The dataset retains every file occurrence with its repository, path, and content hash. It…
Hypothesis Frontier: Verifier Guided LLM and Symbolic Search for First-Order Induction
The paper introduces Hypothesis Frontier, a framework that uses a combination of language models (LLMs) and symbolic processing to solve first-order concept synthesis problems. The system iteratively generates and…
IO Factory: Simulating AI-Enabled Influence Campaigns at Scale
The paper introduces IO Factory, an AI framework designed to simulate information and influence campaigns at scale. The framework is designed to handle not just individual language models but also AI swarms, which are…
Most biomedical publications show signs of LLM-assisted writing
A study suggests that by the end of 2025, approximately 89% of biomedical papers on PubMed Central showed signs of LLM-assisted writing, with a higher usage in the Discussion section compared to the Methods section.
Most biomedical publications show signs of LLM-assisted writing
A study suggests that by the end of 2025, 89% of biomedical papers on PubMed Central showed an excess of language associated with LLM-assisted writing. The authors argue that this could impact future guidelines and…
Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory
The paper presents a proof of quantum coordination advantages in AI state-tracking tasks, specifically in tasks involving semantic compilation and latent memory. It demonstrates that quantum computers can compress…
SkillLens: Visual Skill Cards for Retrieval-Augmented GUI Action Prediction and On-Policy Distillation
Researchers introduce Visual Skill Cards (VSCs), a new method for improving the decision-making abilities of computer agents in GUI environments. VSCs are memory representations that bind reusable procedures with…
SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure
SkillZip is an evaluation-free method that helps compress skills by identifying their shortest faithful structural explanations, making it easier to reuse common action sequences without needing to repeat them. This…
V-FiLLM: Verified Financial LLM Reasoning Benchmark
Researchers have created a new framework called V-FiLLM to evaluate the abilities of Language Models (LLMs) in financial reasoning using structured data. The framework generates questions from executable computation…
VibeLifeBench: Can Your Life Agent Be Proactive and Persistent in a Living World?
Researchers introduce a new benchmark called VibeLifeBench to evaluate large language model (LLM) agents' ability to be proactive and consistent in long-horizon tasks across ten everyday life domains. The benchmark…
Why Does CLAUDE.md Keep Growing? Catastrophic Remembering in Agentic Coding
The research notes discuss a phenomenon called 'catastrophic remembering' in Agentic coding READMEs like CLAUDE.md where instructions grow without bound and do not get deleted easily over time. The paper proposes that…
Why Does CLAUDE.md Keep Growing? Catastrophic Remembering in Agentic Coding
The paper discusses the growth of Agentic coding README files like CLAUDE.md in real repositories and attributes this to imperfect recall. The authors refer to this phenomenon as 'catastrophic remembering'. They find…
Agentic Auto-Research is Fuzz Testing
The authors argue that current autonomous research agents, which generate experiments faster than researchers can validate them, lack the ability to efficiently handle sparse feedback. They propose a solution inspired…
Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy
Researchers propose a verification layer driven by large language models (LLMs) to evaluate the feasibility and ethics of actions suggested by robot planning models before they are executed. The system aims to reduce…
ArchAgent v2: A Case Study with the Data Prefetching Championship
In a study published in 2026, researchers presented ArchAgent v2, a framework that automates the search for multi-level data prefetching in computer microarchitecture. The new version of ArchAgent outperformed…
ArchAgent v2: A Case Study with the Data Prefetching Championship
The paper presents ArchAgent v2, a framework that automates the discovery of multi-level data prefetching in computer microarchitecture. It outperforms hand-designed solutions from the 4th Data Prefetching Championship…
ArchAgent v2: A Case Study with the Data Prefetching Championship
The paper presents ArchAgent v2, a framework that scales automated microarchitecture search to multi-level data prefetching. It outperforms the winning hand-designed solution in the 4th Data Prefetching Championship…
Avalon-ToM-Bench: Evaluating Fine-Grained Theory of Mind via Asymmetric Game Mechanics
Researchers introduce Avalon-ToM-Bench, a new benchmark for evaluating fine-grained Theory of Mind (understanding others' thoughts and motivations) in AI models. The benchmark uses the asymmetric-information mechanics…
Avalon-ToM-Bench: Evaluating Fine-Grained Theory of Mind via Asymmetric Game Mechanics
A new benchmark called Avalon-ToM-Bench is introduced to evaluate fine-grained Theory of Mind (ToM) abilities in agents. The benchmark operates through the asymmetric-information mechanics of a game named The…
Beyond Naturalness: Probing Automated Text-To-Speech Evaluators on Linguistically Grounded Dimensions
Researchers have created a new method for evaluating text-to-speech (TTS) systems by breaking down the concept of 'naturalness' into ten distinct linguistic dimensions. They found that current TTS evaluation methods do…
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