arXiv cs.AI
AURA: Action-Gated Memory for Robot Policies at Constant VRAM
The paper presents AURA-Mem, a novel memory architecture designed for robotic policies that operates with constant…
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arXiv cs.AI
Evaluating Transformer and LSTM Frameworks for Prediction in Ungauged Basins
This study evaluates the effectiveness of Transformer and LSTM frameworks for predicting streamflow in ungauged…
arXiv cs.AI
BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces
The paper introduces BehaviorBench, a benchmark designed to evaluate personalized decision modeling using real-world…
arXiv cs.AI
ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning
ChatHealthAI is a proposed multimodal reasoning framework that aligns electronic health record (EHR) representations…
arXiv cs.AI
Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection
Traj-Evolve is a self-evolving multi-agent system designed for modeling patient trajectories in lung cancer early…
arXiv cs.AI
An Exploration of Collision-based Enemy Morphology Generation
The paper explores novel methods for generating enemy morphologies in video games using player collision information.…
arXiv cs.AI
Thinking Past the Answer: Evaluating Harmful Overthinking in Large Reasoning Models
The paper evaluates the phenomenon of harmful overthinking in Large Reasoning Models (LRMs). It introduces a new…
arXiv cs.AI
Toward a Modular Architecture for Embedded AI Agent Systems at the Edge
The paper discusses a modular architecture for embedded AI agent systems designed to operate within the constraints of…
arXiv cs.AI
Don't Gamble, GAMBLe: An Analytical Framework for AI-Driven Research Systems
The paper titled 'Don't Gamble, GAMBLe' introduces a framework for analyzing AI-Driven Research Systems (ADRS). It…
arXiv cs.AI
When Helping Hurts and How to Fix It: Multi-Agent Debate for Data Cleaning
The paper explores the impact of multi-agent debate on data cleaning processes. It finds that while debate can lead to…
arXiv cs.AI
Handoff Debt: The Rediscovery Cost When Coding Agents Take Over Interrupted Tasks
The paper discusses the concept of 'handoff debt' in coding tasks where agents take over interrupted work. It…
arXiv cs.AI
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
A recent study explores the potential of large AI models in dental healthcare, highlighting the need for a unified…
arXiv cs.AI
What Benchmarks Don't Measure: The Case for Evaluating Abstention Competence in Autonomous Agents
The paper discusses the limitations of current benchmarks for evaluating autonomous agents, particularly their failure…
arXiv cs.AI
WISE-HAR: A Generalizable Ensemble Deep Learning Framework for WiFi-Based Human Activity Recognition
The paper presents WISE-HAR, an ensemble deep learning framework for recognizing human activities using WiFi signals.…
arXiv cs.AI
Inducing Reasoning Primitives from Agent Traces
The paper introduces a method called Reasoning Primitive Induction, which aims to enhance the performance of…
arXiv cs.AI
AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification
The article discusses AuditFlow, a new framework designed for structured financial reporting verification. It utilizes…
arXiv cs.AI
TriEval: A Resource-Efficient Pipeline for LLM Bias, Toxicity, and Truthfulness Assessment
TriEval is a new pipeline designed to assess bias, toxicity, and truthfulness in large language models (LLMs)…
arXiv cs.AI
RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases
The paper introduces RelGT-AC, a new model designed for autocomplete tasks in relational databases. It enhances the…
arXiv cs.AI
ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents
The paper introduces ToolGate, a system designed to improve the efficiency of tool-augmented vision-language agents.…
arXiv cs.AI
SkillDAG: Self-Evolving Typed Skill Graphs for LLM Skill Selection at Scale
The paper introduces SkillDAG, a novel approach for selecting skills in large language models (LLMs) by modeling…
arXiv cs.AI
CORE: Conflict-Oriented Reasoning for General Multimodal Manipulation Detection
The article discusses a new framework called CORE, which stands for Conflict-Oriented Reasoning, designed to enhance…
arXiv cs.AI
DELTAMEM: Incremental Experience Memory for LLM Agents via Residual Trees
The paper introduces DeltaMem, a framework designed to enhance memory management in Large Language Model (LLM) agents.…
arXiv cs.AI
The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
The article discusses a new approach to budget allocation for Large Language Models (LLMs) based on economic…
arXiv cs.AI
Decomposing how prompting steers behavior
The paper titled 'Decomposing how prompting steers behavior' explores how prompting influences the internal…
arXiv cs.AI
From Long News to Accurate Forecast: Importance-Aware Fusion and PRM-Guided Reflection for Time Series Forecasting
A new framework has been developed to enhance time series forecasting by integrating news articles. This approach…
arXiv cs.AI
DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration
The paper titled 'DeskCraft' introduces a new benchmark for evaluating desktop agents in professional workflows that…
arXiv cs.AI
EvoTrainer: Co-Evolving LLM Policies and Training Harnesses for Autonomous Agentic Reinforcement Learning
EvoTrainer is a new autonomous training framework designed for co-evolving LLM policies and training harnesses. It…
arXiv cs.AI
Uncertainty-Aware Clarification in LLM Agents with Information Gain
The article discusses a new framework for Large Language Model (LLM) agents that aims to improve their performance in…
arXiv cs.AI
Think-Before-Speak: From Internal Evaluation to Public Expression in Multi-Agent Social Simulation
The paper introduces a new framework called Think-Before-Speak (TBS) for multi-agent social simulation. TBS separates…
arXiv cs.AI
GTBench: A Curriculum-Grounded Benchmark for Evaluating LLMs as Mathematical Research Assistants in Graph Theory
The article introduces GTBench, a benchmark designed to evaluate large language models (LLMs) as mathematical research…
arXiv cs.AI
ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models
The article introduces ClinicalMC, a benchmark designed for evaluating large language models in multi-course clinical…
arXiv cs.AI
MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents
MedCUA-Bench is a newly introduced benchmark designed specifically for clinical computer-use agents. It aims to…
arXiv cs.AI
Effect of Demographic Bias on Skin Lesion Classification
The study investigates the impact of demographic bias on skin lesion classification using ResNet-based models. It…
arXiv cs.AI
Perceive Before Reasoning: A Pre-Reasoning Perception Framework for Efficient and Reliable Proactive Mobile Agents
The article discusses a new framework called the Pre-Reasoning Perception Framework (PRPF) designed to enhance…
arXiv cs.AI
Solipsistic Superintelligence is Unlikely to be Cooperative
A recent paper argues that superintelligence developed from a solipsistic approach to AI design is unlikely to be…
arXiv cs.AI
Do Real-World Datasets Contain Natural Experiments? An Empirical Study Using Causal Feature Selection
The study investigates whether real-world datasets contain natural experiments, which are implicit interventions…
arXiv cs.AI
Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering
The article discusses a novel approach for enhancing Visual Question Answering (VQA) by distilling rules from Large…
arXiv cs.AI
A Negative Result on Cross-Model Activation Transfer in a Pythia Multi-Hop Setting
The paper presents a negative result regarding cross-model activation transfer in a multi-hop reasoning setting using…
arXiv cs.AI
LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks
The article discusses LEAP, a new framework designed to enhance the capabilities of Large Language Models (LLMs) in…
arXiv cs.AI
The Reliability Gap in Benchmark Auditing: Distribution Shift and Scale as Failure Modes of Contamination Detection
The article discusses the challenges of benchmark auditing in artificial intelligence, particularly regarding…
arXiv cs.AI
The Violation Situation Pattern: A Knowledge-Graph Pattern for Compliance Violations
The Violation Situation Pattern (VSP) is a new knowledge-graph pattern designed to improve compliance violation…
arXiv cs.AI
InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain
The paper introduces InfoMem, a new reward mechanism designed for training long-context memory agents in artificial…
arXiv cs.AI
CP-Agent: Context-Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations
The article introduces CP-Agent, a multimodal large language model designed for cellular morphological profiling under…
arXiv cs.AI
What Makes Interaction Trajectories Effective for Training Terminal Agents?
The paper investigates the effectiveness of interaction trajectories in training terminal agents. It reveals that…
arXiv cs.AI
DMF: A Deterministic Memory Framework for Conversational AI Agents
The Deterministic Memory Framework (DMF) aims to enhance memory systems for conversational AI agents. It replaces…
arXiv cs.AI
StepFinder: A Temporal Semantic Framework for Failure Attribution in Multi-Agent Systems
StepFinder is a new framework designed for failure attribution in multi-agent systems. It aims to improve the…
arXiv cs.AI
A formal definition and meta-model for a machine theory of mind
The paper presents a formal definition and meta-model for the Machine Theory of Mind. It integrates insights from…
arXiv cs.AI
ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
The paper introduces ThoughtFold, a framework designed to improve the efficiency of Large Reasoning Models (LRMs) by…
arXiv cs.AI
Overlaying Governance: A Compositional Authorization Framework for Delegation and Scope in Agentic AI
The paper presents a new compositional authorization framework for managing delegation and scope in agentic AI…
arXiv cs.AI
SAGE: A Quantitative Evaluation of Socialized Evolution in Agent Ecosystems
The paper introduces SAGE, a framework for evaluating socialized evolution in agent ecosystems. It compares two…