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Notes on artificial intelligence
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GUI agent: Guided Exploration of User-Sensitive Screens
This research presents a new agent called Guided Exploration of User-Sensitive Screens (GUI agent) designed to automate tasks within an open Graphical User Interface (GUI) environment. The GUI agent is intended to…
Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization
The paper introduces a framework for comparing different variants of RAG (Rich Automated Generation) scenarios, including GraphRAG and Agentic RAG, in semi-structured knowledge bases. The framework includes nine…
Model Forensics: Investigating Whether Concerning Behavior Reflects Misalignment
The authors propose a method for investigating if AI models are acting with 'malign intent' when exhibiting concerning behavior. The method involves analyzing the chain of thought (CoT) of the AI and making adjustments…
The Unfireable Safety Kernel: Execution-Time AI Alignment for AI Agents and Other Escapable AI Systems
The authors present the Unfireable Safety Kernel, a Rust implementation that serves as an execution-time AI alignment layer for escapable AI systems. This system aims to provide authorization mechanisms for controlling…
Uncertainty Quantification for Computer-Use Agents: A Benchmark across Vision-Language Models and GUI Grounding Datasets
Researchers have developed a benchmark called Argus to test the reliability of computer-use agents that convert vision-language model predictions into executable clicks. The study compares 27 methods across four…
DeepBD: A Grounded Agentic Workflow for Variant Prioritization and Diagnosis of Genetic Birth Defects
Researchers present DeepBD, an AI system designed to help diagnose genetic birth defects by prioritizing patient-specific candidate variants. The system uses a workflow with various components such as rule evidence…
NoContactNoWorries: Estimating Contact through Vision and Proprioception for In-Hand Dexterous Manipulation
Researchers have developed a transformer-based multimodal framework named NoContactNoWorries that allows robots to infer binary contact states from RGB-D vision and the robot's proprioception. This approach offers a…
OpenThoughts-Agent: Data Recipes for Agentic Models
The OpenThoughts-Agent project presents a fully open data curation pipeline for training agentic models, which are language models that expand AI applications. The project conducted controlled ablation experiments and…
Paying to Know: Micro-Transaction Markets for Verified Product Information in Agentic E-Commerce
The authors propose a new model for e-commerce where buyers use micro-payments to access detailed, verified information about products from sellers and reviewers. This model is designed for autonomous agent shoppers…
Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams
This research explores the use of large language models (LLMs) in detecting scam phone calls in Turkish, a low-resource language where such detection is particularly challenging due to limited annotated data and…
Visualizing 'We the People': Bridging the Perception Gap through Pluralistic Data Storytelling
The paper discusses a project that used AI to create interactive 'opinion landscapes' for an online deliberation called 'We the People'. The goal was to provide a more nuanced and collaborative way of visualizing…
AI Exposure Scores: what they measure, what they miss, and what comes next
The article discusses the limitations of a set of AI Exposure Scores introduced by Eloundou et al., which measure the share of tasks that can be assisted by large language models. The authors highlight two main gaps…
Detecting Malicious Agent Skills in the Wild using Attention
The research presents a two-stage detector called Locate-and-Judge for identifying malicious skills in Language Model (LLM) agents. These skills are third-party packages of instructions that can potentially exfiltrate…
GIF: Locally Sound Geometric Information Flow Control for LLMs
Researchers present a new framework called Geometric Information Flow (GIF) for tracking information flow from input tokens to outputs in large language models. This framework uses the Jacobian and local output…
Learning Process Rewards via Success Visitation Matching for Efficient RL
Researchers propose a method to make reinforcement learning (RL) more effective when dealing with sparse rewards, which are typically given only when a task is completed. The method incentivizes the RL-learned policy…
PsyBridge: A Hybrid Intelligent Framework for Multi-Dimensional Mental Health Assessment and Decision Support
The study proposes a new framework called PsyBridge, designed to improve mental health assessment by integrating multiple dimensions, including clinically validated screening tools, cognitive evaluation, and…
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