Search: “tools”

Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generation

arXiv:2604.16958v1 Announce Type: new Abstract: Narrative-driven product photography has become a prevalent paradigm in modern marketing, as coherent visual storytelling helps convey product value and

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Stop Tracking Me! Proactive Defense Against Attribute Inference Attack in LLMs

DGX agent

arXiv:2602.11528v2 Announce Type: replace-cross Abstract: Recent studies have shown that large language models (LLMs) can infer private user attributes (e.g., age, location, gender) from user-generate

researcharxiv-cs-cl

21 Apr 2026

ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding

arXiv:2510.00546v5 Announce Type: replace Abstract: Large Reasoning Models (LRMs) allocate substantial inference-time compute to Chain-of-Thought (CoT) reasoning, improving performance on mathematics,

Unified Ultrasound Intelligence Toward an End-to-End Agentic System

arXiv:2604.16914v1 Announce Type: new Abstract: Clinical ultrasound analysis demands models that generalize across heterogeneous organs, views, and devices, while supporting interpretable workflow-lev

VIDS: A Verified Imaging Dataset Standard for Medical AI

model-releasesarxiv-cs-cv

arXiv:2604.17525v1 Announce Type: cross Abstract: Medical imaging AI development is fundamentally dependent on annotated datasets, yet no existing standard provides machine-enforceable validation acro

Where to Focus: Query-Modulated Multimodal Keyframe Selection for Long Video Understanding

arXiv:2604.17422v1 Announce Type: new Abstract: Long video understanding remains a formidable challenge for Multimodal Large Language Models (MLLMs) due to the prohibitive computational cost of proces

local-aiarxiv-cs-cv

AgentV-RL: Scaling Reward Modeling with Agentic Verifier

arXiv:2604.16004v1 Announce Type: cross Abstract: Verifiers have been demonstrated to enhance LLM reasoning via test-time scaling (TTS). Yet, they face significant challenges in complex domains. Error

COMPASS: Benchmarking Constrained Optimization in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2510.07043v2 Announce Type: replace Abstract: Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shop

FACTS: Table Summarization via Offline Template Generation with Agentic Workflows

arXiv:2510.13920v2 Announce Type: replace Abstract: Query-focused table summarization requires generating natural language summaries of tabular data conditioned on a user query, enabling users to acce

Safety

Find, Fix, Reason: Context Repair for Video Reasoning

arXiv:2604.16243v1 Announce Type: new Abstract: Reinforcement learning has advanced video reasoning in large multi-modal models, yet dominant pipelines either rely on on-policy self-exploration, which

safetyarxiv-cs-cv

KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction

arXiv:2602.07303v3 Announce Type: replace-cross Abstract: Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions w

local-aiarxiv-cs-ai

LaMSUM: Amplifying Voices Against Harassment through LLM Guided Extractive Summarization of User Incident Reports

arXiv:2406.15809v5 Announce Type: replace Abstract: Citizen reporting platforms help the public and authorities stay informed about sexual harassment incidents. However, the high volume of data shared

LinuxArena: A Control Setting for AI Agents in Live Production Software Environments

arXiv:2604.15384v1 Announce Type: cross Abstract: We introduce LinuxArena, a control setting in which agents operate directly on live, multi-service production environments. LinuxArena contains 20 env

MemEvoBench: Benchmarking Memory MisEvolution in LLM Agents

arXiv:2604.15774v1 Announce Type: new Abstract: Equipping Large Language Models (LLMs) with persistent memory enhances interaction continuity and personalization but introduces new safety risks. Speci

PolicyBank: Evolving Policy Understanding for LLM Agents

arXiv:2604.15505v1 Announce Type: cross Abstract: LLM agents operating under organizational policies must comply with authorization constraints typically specified in natural language. In practice, su

Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP

arXiv:2602.11327v2 Announce Type: replace-cross Abstract: The rapid development of the AI agent communication protocols, including the Model Context Protocol (MCP), Agent2Agent (A2A), Agora, and Agent

SENSE: Stereo OpEN Vocabulary SEmantic Segmentation

arXiv:2604.15946v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation enables models to segment objects or image regions beyond fixed class sets, offering flexibility in dynamic enviro

VeriGraph: Scene Graphs for Execution Verifiable Robot Planning

arXiv:2411.10446v3 Announce Type: replace-cross Abstract: Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrec

Beyond Translation: Evaluating Mathematical Reasoning Capabilities of LLMs in Sinhala and Tamil

arXiv:2602.14517v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved strong results in mathematical reasoning, and are increasingly deployed as tutoring and learning support

Does RL Expand the Capability Boundary of LLM Agents? A PASS@(k,T) Analysis

arXiv:2604.14877v1 Announce Type: new Abstract: Does reinforcement learning genuinely expand what LLM agents can do, or merely make them more reliable? For static reasoning, recent work answers the se

agentsarxiv-cs-lg

EchoAgent: Towards Reliable Echocardiography Interpretation with 'Eyes','Hands' and 'Minds'

arXiv:2604.05541v2 Announce Type: replace Abstract: Reliable interpretation of echocardiography (Echo) is crucial for assessing cardiac function, which demands clinicians to synchronously orchestrate

From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench

arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning

arXiv:2603.01410v2 Announce Type: replace Abstract: Knowledge graphs provide structured and reliable information for many real-world applications, motivating increasing interest in combining large lan

HUOZIIME: An On-Device LLM-enhanced Input Method for Deep Personalization

arXiv:2604.14159v1 Announce Type: new Abstract: Mobile input method editors (IMEs) are the primary interface for text input, yet they remain constrained to manual typing and struggle to produce person

local-aiarxiv-cs-cl

Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making

arXiv:2604.14240v1 Announce Type: cross Abstract: The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models p

agentsarxiv-cs-lg

MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents

arXiv:2509.06477v2 Announce Type: replace Abstract: Shortcuts such as APIs and deep-links have emerged as efficient complements to flexible GUI operations, fostering a promising hybrid paradigm for ML

Rethinking AI Hardware: A Three-Layer Cognitive Architecture for Autonomous Agents

arXiv:2604.13757v1 Announce Type: new Abstract: The next generation of autonomous AI systems will be constrained not only by model capability, but by how intelligence is structured across heterogeneou

local-aiarxiv-cs-ai

Rethinking Patient Education as Multi-turn Multi-modal Interaction

arXiv:2604.14656v1 Announce Type: cross Abstract: Most medical multimodal benchmarks focus on static tasks such as image question answering, report generation, and plain-language rewriting. Patient ed

SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing

arXiv:2604.14399v1 Announce Type: new Abstract: Autonomous on-orbit servicing demands embodied agents that perceive through visual sensors, reason about 3D spatial situations, and execute multi-phase

agentsarxiv-cs-ro

The Cost of Language: Centroid Erasure Exposes and Exploits Modal Competition in Multimodal Language Models

arXiv:2604.14363v1 Announce Type: new Abstract: Multimodal language models systematically underperform on visual perception tasks, yet the structure underlying this failure remains poorly understood.

local-aiarxiv-cs-cl

V-Reflection: Transforming MLLMs from Passive Observers to Active Interrogators

arXiv:2604.03307v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success, yet they remain prone to perception-related hallucinations in fine-graine

local-aiarxiv-cs-cv

A closer look at how large language models trust humans: patterns and biases

arXiv:2504.15801v2 Announce Type: replace Abstract: As large language models (LLMs) and LLM-based agents increasingly interact with humans in decision-making contexts, understanding the trust dynamics

Applications

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning

arXiv:2507.01976v2 Announce Type: replace-cross Abstract: Synthetic network traffic generation has emerged as a promising alternative for various data-driven applications in the networking domain. It

applicationsarxiv-cs-lg

AgentSPEX: An Agent SPecification and EXecution Language

arXiv:2604.13346v1 Announce Type: new Abstract: Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reaso

InfiniteScienceGym: An Unbounded, Procedurally-Generated Benchmark for Scientific Analysis

arXiv:2604.13201v1 Announce Type: new Abstract: Large language models are emerging as scientific assistants, but evaluating their ability to reason from empirical data remains challenging. Benchmarks

Mitigating Barren Plateaus in Quantum Denoising Diffusion Probabilistic Model

arXiv:2512.06695v2 Announce Type: replace Abstract: Quantum generative models exploit quantum superposition and entanglement to enhance learning efficiency for both classical and quantum data. Recentl

researcharxiv-cs-lg

Multi-Agent Object Detection Framework Based on Raspberry Pi YOLO Detector and Slack-Ollama Natural Language Interface

arXiv:2604.13345v1 Announce Type: new Abstract: The paper presents design and prototype implementation of an edge based object detection system within the new paradigm of AI agents orchestration. It g

local-aiarxiv-cs-cv

WebXSkill: Skill Learning for Autonomous Web Agents

arXiv:2604.13318v1 Announce Type: cross Abstract: Autonomous web agents powered by large language models (LLMs) have shown promise in completing complex browser tasks, yet they still struggle with lon

Agentic Control in Variational Language Models

arXiv:2604.12513v1 Announce Type: new Abstract: We study whether a variational language model can support a minimal and measurable form of agentic control grounded in its own internal evidence. Our mo

local-aiarxiv-cs-lg

Agentic Discovery with Active Hypothesis Exploration for Visual Recognition

arXiv:2604.12999v1 Announce Type: new Abstract: We introduce HypoExplore, an agentic framework that formulates neural architecture discovery for visual recognition as a hypothesis-driven scientific in

Agentic Insight Generation in VSM Simulations

arXiv:2604.12421v1 Announce Type: new Abstract: Extracting actionable insights from complex value stream map simulations can be challenging, time-consuming, and error-prone. Recent advances in large l

ARGOS: Who, Where, and When in Agentic Multi-Camera Person Search

arXiv:2604.12762v1 Announce Type: cross Abstract: We introduce ARGOS, the first benchmark and framework that reformulates multi-camera person search as an interactive reasoning problem requiring an ag

Coding-Free and Privacy-Preserving MCP Framework for Clinical Agentic Research Intelligence System

arXiv:2604.12258v1 Announce Type: cross Abstract: Clinical research involves labor-intensive processes such as study design, cohort construction, model development, and documentation, requiring domain

Cooperative Memory Paging with Keyword Bookmarks for Long-Horizon LLM Conversations

arXiv:2604.12376v1 Announce Type: cross Abstract: When LLM conversations grow beyond the context window, old content must be evicted -- but how does the model recover it when needed? We propose cooper

Safety

Cycle-Consistent Search: Question Reconstructability as a Proxy Reward for Search Agent Training

arXiv:2604.12967v1 Announce Type: new Abstract: Reinforcement Learning (RL) has shown strong potential for optimizing search agents in complex information retrieval tasks. However, existing approaches

safetyarxiv-cs-ai

Evaluating Language Models for Harmful Manipulation

arXiv:2603.25326v4 Announce Type: replace Abstract: Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a f

local-aiarxiv-cs-ai

Safety

GUIDE: Guided Updates for In-context Decision Evolution in LLM-Driven Spacecraft Operations

arXiv:2603.27306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been proposed as supervisory agents for spacecraft operations, but existing approaches rely on static prompt

safetyarxiv-cs-ai

Applications

MedGS: Gaussian Splatting for Multi-Modal 3D Medical Imaging

arXiv:2509.16806v4 Announce Type: replace Abstract: Endoluminal endoscopic procedures are essential for diagnosing colorectal cancer and other severe conditions in the digestive tract, urogenital syst

applicationsarxiv-cs-cv