Search: “agents”

RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine

arXiv:2410.13987v3 Announce Type: replace Abstract: Answering complex real-world questions in the medical domain often requires accurate retrieval from medical Textual Knowledge Graphs (medical TKGs),

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Safety

Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty

DGX agent

arXiv:2508.21322v2 Announce Type: replace Abstract: Achieving both safety guarantees and real-time performance in cooperative vehicle coordination remains a fundamental challenge, particularly in dyna

safetyarxiv-cs-ro

14 Apr 2026

See Fair, Speak Truth: Equitable Attention Improves Grounding and Reduces Hallucination in Vision-Language Alignment

arXiv:2604.09749v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) frequently hallucinate objects that are absent from the visual input, often because attention during decoding i

Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks

arXiv:2604.11610v1 Announce Type: new Abstract: As LLM-based assistants become persistent and personalized, they must extract and retain useful information from past conversations as memory. However,

SHE: Stepwise Hybrid Examination Reinforcement Learning Framework for E-commerce Search Relevance

arXiv:2510.07972v3 Announce Type: replace Abstract: Query-product relevance prediction is vital for AI-driven e-commerce, yet current LLM-based approaches face a dilemma: SFT and DPO struggle with lon

Thought Branches: Interpreting LLM Reasoning Requires Resampling

arXiv:2510.27484v2 Announce Type: replace-cross Abstract: Most work interpreting reasoning models studies only a single chain-of-thought (CoT), yet these models define distributions over many possible

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale

arXiv:2604.10291v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown promising performance in time series modeling tasks, but do they truly understand time series data? While multip

Towards Adaptive Open-Set Object Detection via Category-Level Collaboration Knowledge Mining

arXiv:2604.11195v1 Announce Type: cross Abstract: Existing object detectors often struggle to generalize across domains while adapting to emerging novel categories. Adaptive open-set object detection

Tuning Qwen2.5-VL to Improve Its Web Interaction Skills

arXiv:2604.09571v1 Announce Type: cross Abstract: Recent advances in vision-language models (VLMs) have sparked growing interest in using them to automate web tasks, yet their feasibility as independe

Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control

arXiv:2604.03147v2 Announce Type: replace-cross Abstract: We present a method to identify a valence-arousal (VA) subspace within large language model representations. From 211k emotion-labeled texts,

Local Ai

WebLLM: A High-Performance In-Browser LLM Inference Engine

arXiv:2412.15803v2 Announce Type: replace-cross Abstract: Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-gra

local-aiarxiv-cs-ai

What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction

arXiv:2407.08101v4 Announce Type: replace Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, wher

When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs

arXiv:2604.10062v1 Announce Type: new Abstract: We study reward poisoning attacks in reinforcement learning (RL), where an adversary manipulates rewards within constrained budgets to force the target

Who Gets Which Message? Auditing Demographic Bias in LLM-Generated Targeted Text

arXiv:2601.17172v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly capable of generating personalized, persuasive text at scale, raising new questions about bias a

Why Smaller Is Slower? Dimensional Misalignment in Compressed LLMs

arXiv:2604.09595v1 Announce Type: cross Abstract: Post-training compression reduces LLM parameter counts but often produces irregular tensor dimensions that degrade GPU performance -- a phenomenon we

ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval

arXiv:2604.10898v1 Announce Type: new Abstract: Large language models (LLMs) have shown great performance on complex reasoning tasks but often require generating long intermediate thoughts before reac

Advantage-Guided Diffusion for Model-Based Reinforcement Learning

arXiv:2604.09035v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) with autoregressive world models suffers from compounding errors, whereas diffusion world models mitigate this

ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization

model-releasesarxiv-cs-lg

arXiv:2603.21180v3 Announce Type: replace Abstract: Sequential experimental design under expensive, gradient-free objectives is a central challenge in computational statistics: evaluation budgets are

Applications

AniGen: Unified S^3 Fields for Animatable 3D Asset Generation

arXiv:2604.08746v1 Announce Type: cross Abstract: Animatable 3D assets, defined as geometry equipped with an articulated skeleton and skinning weights, are fundamental to interactive graphics, embodie

applicationsarxiv-cs-cv

AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention

arXiv:2511.18960v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have shown remarkable progress in embodied tasks recently, but most methods process visual observations in

Balancing User Preferences by Social Networks: A Condition-Guided Social Recommendation Model for Mitigating Popularity Bias

arXiv:2405.16772v2 Announce Type: replace-cross Abstract: Social recommendation models weave social interactions into their design to provide uniquely personalized recommendation results for users. Ho

CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention

arXiv:2603.18561v2 Announce Type: replace Abstract: Planning-oriented end-to-end driving models show great promise, yet they fundamentally learn statistical correlations instead of true causal relatio

Chain-in-Tree: Back to Sequential Reasoning in LLM Tree Search

arXiv:2509.25835v4 Announce Type: replace Abstract: Test-time scaling improves large language models (LLMs) on long-horizon reasoning tasks by allocating more compute at inference. LLM inference via t

Tutorials

Detection and Characterization of Coordinated Online Behavior: A Survey

arXiv:2408.01257v2 Announce Type: replace-cross Abstract: Coordination is a fundamental aspect of life. The advent of social media has made it integral also to online human interactions, such as those

tutorialsarxiv-cs-ai

E3-TIR: Enhanced Experience Exploitation for Tool-Integrated Reasoning

arXiv:2604.09455v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated significant potential in Tool-Integrated Reasoning (TIR), existing training paradigms face signific

EgoTL: Egocentric Think-Aloud Chains for Long-Horizon Tasks

arXiv:2604.09535v1 Announce Type: new Abstract: Large foundation models have made significant advances in embodied intelligence, enabling synthesis and reasoning over egocentric input for household ta

EmoCtrl: Controllable Emotional Image Content Generation

arXiv:2512.22437v2 Announce Type: replace Abstract: An image conveys meaning through both its visual content and emotional tone, jointly shaping human perception. We introduce Controllable Emotional I

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving

arXiv:2603.13842v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving is typically built upon imitation learning (IL), yet its performance is constrained by the quality of human demo

FIT-GNN: Faster Inference Time for GNNs that 'FIT' in Memory Using Coarsening

model-releasesarxiv-cs-lg

arXiv:2410.15001v5 Announce Type: replace Abstract: Scalability of Graph Neural Networks (GNNs) remains a significant challenge. To tackle this, methods like coarsening, condensation, and computation

Tutorials

LEGO: Latent-space Exploration for Geometry-aware Optimization of Humanoid Kinematic Design

arXiv:2604.08636v1 Announce Type: cross Abstract: Designing robot morphologies and kinematics has traditionally relied on human intuition, with little systematic foundation. Motion-design co-optimizat

tutorialsarxiv-cs-ai

Listener-Rewarded Thinking in VLMs for Image Preferences

arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving

arXiv:2604.08719v1 Announce Type: cross Abstract: Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck

Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space

model-releasesarxiv-cs-lg

arXiv:2501.15461v4 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown great success in various graph-based learning tasks. However, it often faces the issue of over-smoothing as

MedConceal: A Benchmark for Clinical Hidden-Concern Reasoning Under Partial Observability

arXiv:2604.08788v1 Announce Type: new Abstract: Patient-clinician communication is an asymmetric-information problem: patients often do not disclose fears, misconceptions, or practical barriers unless

Policy-Aware Design of Large-Scale Factorial Experiments

arXiv:2604.08804v1 Announce Type: cross Abstract: Digital firms routinely run many online experiments on shared user populations. When product decisions are compositional, such as combinations of inte

RAMP: Hybrid DRL for Online Learning of Numeric Action Models

arXiv:2604.08685v1 Announce Type: new Abstract: Automated planning algorithms require an action model specifying the preconditions and effects of each action, but obtaining such a model is often hard.

Research

Robust Adaptive Backstepping Impedance Control of Robots in Unknown Environments

arXiv:2604.09323v1 Announce Type: new Abstract: This paper presents a Robust Adaptive Backstepping Impedance Control (RABIC) strategy for robots operating in contact-rich and uncertain environments. T

researcharxiv-cs-ro

Applications

SatQNet: Satellite-assisted Quantum Network Entanglement Routing Using Directed Line Graph Neural Networks

arXiv:2604.09306v1 Announce Type: cross Abstract: Quantum networks are expected to become a key enabler for interconnecting quantum devices. In contrast to classical communication networks, however, i

applicationsarxiv-cs-ai

SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks

arXiv:2604.08865v1 Announce Type: new Abstract: Proximal Policy Optimization (PPO) is central to aligning Large Language Models (LLMs) in reasoning tasks with verifiable rewards. However, standard tok

The AI Codebase Maturity Model: From Assisted Coding to Self-Sustaining Systems

arXiv:2604.09388v1 Announce Type: cross Abstract: AI coding tools are widely adopted, but most teams plateau at prompt-and-review without a framework for systematic progression. This paper presents th

The Hot Mess of AI: How Does Misalignment Scale With Model Intelligence and Task Complexity?

arXiv:2601.23045v2 Announce Type: replace Abstract: As AI becomes more capable, we entrust it with more general and consequential tasks. The risks from failure grow more severe with increasing task sc

The Two-Stage Decision-Sampling Hypothesis: Understanding the Emergence of Self-Reflection in RL-Trained LLMs

arXiv:2601.01580v2 Announce Type: replace-cross Abstract: Self-reflection capabilities emerge in Large Language Models after RL post-training, with multi-turn RL achieving substantial gains over SFT c

UAV-Track VLA: Embodied Aerial Tracking via Vision-Language-Action Models

arXiv:2604.02241v2 Announce Type: replace Abstract: Embodied visual tracking is crucial for Unmanned Aerial Vehicles (UAVs) executing complex real-world tasks. In dynamic urban scenarios with complex

Why Adam Can Beat SGD: Second-Moment Normalization Yields Sharper Tails

arXiv:2603.03099v5 Announce Type: replace-cross Abstract: Despite Adam demonstrating faster empirical convergence than SGD in many applications, much of the existing theory yields guarantees essential

Tutorials

WOMBET: World Model-based Experience Transfer for Robust and Sample-efficient Reinforcement Learning

arXiv:2604.08958v1 Announce Type: cross Abstract: Reinforcement learning (RL) in robotics is often limited by the cost and risk of data collection, motivating experience transfer from a source task to

tutorialsarxiv-cs-ai

3DrawAgent: Teaching LLM to Draw in 3D with Early Contrastive Experience

arXiv:2604.08042v1 Announce Type: new Abstract: Sketching in 3D space enables expressive reasoning about shape, structure, and spatial relationships, yet generating 3D sketches through natural languag

10 Apr 2026

A Giant-Step Baby-Step Classifier For Scalable and Real-Time Anomaly Detection In Industrial Control Systems and Water Treatment Systems

arXiv:2504.20906v4 Announce Type: replace-cross Abstract: The continuous monitoring of the interactions between cyber-physical components of any industrial control system (ICS) is required to secure a

10 Apr 2026

Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference

arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s