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2,343 notes. Notes 401 to 450, page 9 of 47.
VICBench: A Multi-Language Benchmark for Code Vulnerability Detection
The paper introduces VICBench, a new benchmark dataset for evaluating code vulnerability detection tools. VICBench contains 100 verified vulnerability-inducing commits (VICs) across 88 projects in Python, Java, and…
VICBench: A Multi-Language Benchmark for Code Vulnerability Detection
Researchers have created a benchmark dataset called VICBench for evaluating code vulnerability detection tools. The dataset contains 100 verified vulnerabilities across 88 projects in Python, Java, and C++, covering 48…
VICBench: A Multi-Language Benchmark for Code Vulnerability Detection
The paper introduces VICBench, a multi-language benchmark for code vulnerability detection. It was created by human experts and an agentic workflow, featuring 100 verified vulnerabilities across 88 projects in Python…
Who Thinks Best Depends on How Long You Let Them: Budget-Dependent Rankings in LLM Evaluation
An evaluation study examining how token budgets affect model accuracy and comparative rankings.
A Comparative Evaluation of Deep Learning Object Detection Models on a Real-World Multi-Plant Dataset from Africa
A study compares six object detection models on a dataset collected from Nigerian farms, called AgriAISeg, which includes sesame, cabbage, and tomato crops under varying environmental conditions. The models tested are…
A Gateway Architecture for Enterprise MCP Authentication: Unifying Heterogeneous Auth, Identity Delegation, and the User / Non-User Persona Problem
The paper discusses a solution to a governance crisis caused by the rapid adoption of Model Context Protocol (MCP) for connecting LLM agents with enterprise tools. The solution is a centralized MCP gateway that…
A Gateway Architecture for Enterprise MCP Authentication: Unifying Heterogeneous Auth, Identity Delegation, and the User / Non-User Persona Problem
This research presents a solution to the governance crisis caused by the rapid adoption of Model Context Protocol (MCP) in large organizations. The proposed solution is a centralized MCP gateway that unifies…
ChemWorld: Programmable Chemical Worlds for Controlled and Replayable Agent Experimentation
The paper introduces ChemWorld, a programmable chemical environment designed for repeatable and controllable agent experimentation in autonomous chemistry. The environment allows researchers to compile reusable process…
ChemWorld: Programmable Chemical Worlds for Controlled and Replayable Agent Experimentation
The paper introduces ChemWorld, a programmable chemical environment that allows researchers to create executable worlds with reusable components. This environment separates the experimental contract available to an…
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…
Conversational Orchestration for Organic 6G
The text discusses a proposed lightweight, decentralized conversational orchestration framework for the 'Organic 6G' network using Large Language Model (LLM)-driven domain agents. The framework aims to simplify service…
Conversational Orchestration for Organic 6G
The authors propose a lightweight, decentralized conversational orchestration framework using Large Language Model (LLM)-driven domain agents for the future network of networks, Organic 6G. The aim is to provide…
DuplexWorld: Can voice agents help you get through the day?
The research paper DuplexWorld evaluates voice agents' performance in various mundane activities like banking, insurance, travel, healthcare, logistics, and pathfinding. The evaluation includes 156 scenarios testing…
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…
Entropy-Centric Explainable AI for Remote Sensing Image Segmentation
The provided text discusses a new Explainable AI (XAI) method for semantic image segmentation in remote sensing, which aims to increase transparency and trust in AI models. The proposed method is based on entropy and…
Entropy-Centric Explainable AI for Remote Sensing Image Segmentation
This research paper introduces an explainable AI (XAI) method for image segmentation in remote sensing. The method is centered around entropy and aims to provide insights into the decision-making process of AI models…
EvoMem: Memory-Augmented Evolution for Code Optimization
The paper introduces EvoMem, a memory architecture for Long Learning Machine (LLM) based evolutionary program search. EvoMem captures and reuses knowledge from successful mutation events to improve the efficiency of…
GitSkills: A Dataset of Agent Skills on GitHub
Researchers present GitSkills, a dataset containing over 3 million skill files for language-model agents found in public GitHub repositories in July 2026. The dataset retains every file occurrence with its repository…
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…
How to Verify Consistency of Probabilistic Claims
Researchers propose an interactive protocol that allows a polynomial-time verifier to check the approximate consistency of a probabilistic predictor's answers in polynomial time. The protocol is relevant for AI safety…
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…
IO Factory: Simulating AI-Enabled Influence Campaigns at Scale
The authors introduce IO Factory, an AI-driven framework for simulating complex information and influence campaigns at scale. These campaigns involve AI swarms that adapt to platform feedback and disguise organized…
MIRA: Medical Image Reflection for Agentic Diagnosis
Researchers present MIRA, a medical image diagnosis framework that allows an autonomous agent to search for relevant evidence, verify the relevance and consistency of the acquired evidence, and adapt its tool-use…
MIRA: Medical Image Reflection for Agentic Diagnosis
The paper introduces MIRA (Medical Image Reflection for Agentic Diagnosis), a medical visual diagnostic framework designed to autonomously search for evidence and verify its relevance and consistency in image…
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…
Multiclass Sentiment Analysis for Identifying Political Viewpoints
Researchers developed two machine-learning models to analyze political viewpoints from social media posts. The XGBoost model achieved an F1-score of 0.2835, and the BERT-based model achieved an F1-score of 0.2806 in a…
MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams
The researchers present MVTrack, a fast moving object tracker that works directly on H.264 bitstreams without needing to reconstruct pixels. It outperforms YOLO26n in terms of parameters, FLOPs, and CPU latency when…
Policy Convergence and Divergence Across National and Within Regional AI Strategies: A Policy Design Element Analysis
The paper analyzes national and regional AI strategies of various countries, finding strong horizontal convergence in economic competitiveness, research support, and ethical AI use. However, there is persistent…
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…
R4DSG: Relative 4D Scene Graph Memory for Object-Centric Question Answering in Long Egocentric Video
Researchers present R4DSG, a relative 4D scene graph memory for long egocentric videos that helps answer object-centric questions more effectively. Unlike previous methods, R4DSG preserves persistent object identity…
R4DSG: Relative 4D Scene Graph Memory for Object-Centric Question Answering in Long Egocentric Video
The paper introduces R4DSG, a method to create a compact and queryable memory for long egocentric video, which is useful for wearable AI assistants. It focuses on preserving persistent object identity and structured…
ReLTEx: Reliable LLM-based Taxonomy Expansion
The paper discusses a new framework called ReLTEx for improving the reliability of Large Language Model (LLM)-based taxonomy expansion. The framework combines LLM-driven candidate generation with structure-aware…
Rule of Thumb: Explaining Artificial Intelligence Systems using Partial Information
The paper presents a new method called 'Rule of Thumb' (RoT) for explaining how Artificial Intelligence systems make decisions. RoT identifies the most relevant features of an AI system to predict its behavior for a…
Rule of Thumb: Explaining Artificial Intelligence Systems using Partial Information
Researchers propose a new approach called 'Rule of Thumb' (RoT) explanations for Explainable Artificial Intelligence (XAI). This method identifies the most relevant features that influence an AI system's behavior for a…
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…
SkillLens: Visual Skill Cards for Retrieval-Augmented GUI Action Prediction and On-Policy Distillation
The paper introduces Visual Skill Cards (VSCs), a memory representation that helps computer agents make decisions by binding reusable procedures with applicability cues, visual evidence, and verification signals. The…
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…
SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure
The paper presents SkillZip, an evaluation-free method for compressing skills used by self-evolving agents. SkillZip aims to make skill compression more efficient by finding the shortest faithful structural explanation…
SkillZip: Evaluation-Free Skill Compression for Self-Evolving Agents by Discovering Reusable Structure
The paper presents SkillZip, an evaluation-free method for compressing skills by finding their shortest faithful structural explanations. It aims to reduce the repetition and expense of injecting and maintaining skills…
sLTN: Structural Logic Tensor Networks
The paper introduces sLTN, an extension of Logic Tensor Networks (LTN), which is a neurosymbolic framework that combines first-order logic with tensor operations for differentiable learning. The new version can handle…
Smart Enough to Go Extinct? An Evolutionary Challenge to the Value of General Intelligence and Its Ethical Implications for AGI
This research paper questions the inherent value of general artificial intelligence (AGI) by comparing its adaptive value to that of simpler life forms like cyanobacteria and horseshoe crabs. The author argues that the…
Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning
The study introduces Surgical WAM, a model that uses unlabeled surgical videos for pre-training and then fine-tunes on a fixed number of labeled demonstrations. The goal is to improve the success rate in closed-loop…
Test-Time Self-Evolving GUI Visual Grounding via Reflection-Guided On-Policy Self-Distillation
The authors propose a new framework called Test-Time Self-Evolving for GUI (Graphical User Interface) Visual Grounding. This method allows models to improve after deployment without the need for human-annotated ground…
Test-Time Self-Evolving GUI Visual Grounding via Reflection-Guided On-Policy Self-Distillation
The paper proposes a Test-Time Self-Evolving framework that allows GUI agents to adapt and improve after deployment without requiring human-annotated ground truth data. The framework includes four components…
The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary Election
The study examines the use of Generative Artificial Intelligence (GenAI) in Norwegian newsrooms during the 2025 parliamentary election and identifies potential risks and challenges associated with it.
Tree-of-Ideas: Automated Research Ideation via Cross-Trajectory Reasoning over Scholarly Evolution
The paper introduces Tree-of-Ideas (ToI), a framework to help with research ideation by tracking and analyzing how research problems and solutions evolve across different scholarly trajectories. ToI outperforms…
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