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2,348 notes and 295 topics.
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2,348 notes, page 20 of 98
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?
The paper introduces VibeLifeBench, a new benchmark for evaluating large language model (LLM) agents' ability to handle long-horizon tasks in everyday life scenarios. The benchmark consists of 200 multi-week timeline…
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…
Whisper-Aware LLM: Self-Supervised Uncertainty Learning for Robust Whispered Speech Recognition
The Whisper-Aware LLM is a new framework designed to improve the performance of ASR (Automatic Speech Recognition) systems for whispered speech. The model learns to perceive and react to the uncertainty associated with…
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…
Workflow Cards: Structured Summaries of Workflow Executions Using Provenance Data
The paper introduces Workflow Cards, a new type of structured summary for machine learning artifacts that focus on workflow executions, which are currently overlooked in Model and Data Cards. Workflow Cards aim to…
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 Auto-Research is Fuzz Testing
The authors argue that current methods for autonomous research agents, which generate experiments and rank them based on learned judges or human reviewers, miss the problem of sparse feedback. They suggest that these…
Agentic Auto-Research is Fuzz Testing
The authors argue that current methods for autonomous research agents are inefficient due to the slow validation process of generated experiments. They propose to adapt fuzzer techniques, which use feedback from…
Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy
The authors propose a system that uses large language models (LLMs) to evaluate the permissibility of actions planned by robots before they are executed. The system aims to reduce risks associated with biased planning…
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…
Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy
Researchers propose a verification layer using large language models (LLMs) to ensure the feasibility and ethical alignment of actions planned by robot autonomy systems. The system can evaluate the permissibility of…
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…
BDH-CQ: In-Context Learning with Recurrent Latent Reasoning
The paper introduces BDH-CQ, a model that combines in-context learning and recurrent latent reasoning. The model updates its memory based on inputs presented during inference, solves queries through iterative…
Beyond Naturalness: Probing Automated Text-To-Speech Evaluators on Linguistically Grounded Dimensions
Researchers create a new evaluation benchmark for Text-to-Speech (TTS) systems to measure their performance on specific linguistic dimensions beyond simple 'naturalness'. They find that current methods struggle to…
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…
CARD: Controlled Agentic Reddit Discussions for Credit Card Simulation
The authors introduce a framework called CARD for generating realistic credit card discussion threads on online platforms, such as Reddit. The framework takes into account various factors like reply structure, comment…
CARD: Controlled Agentic Reddit Discussions for Credit Card Simulation
Researchers introduce CARD, a framework for creating realistic simulations of online credit card discussion threads. This system takes into account various factors such as reply structure, comment function, stance…
CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems
The paper proposes a modular cognitive architecture for developing intelligent virtual agents (IVAs) that can function effectively in real-time interactive virtual environments. The proposed architecture aims to bridge…
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.
