Search: “agents”

Deep Optimizer States: Towards Scalable Training of Transformer Models Using Interleaved Offloading

arXiv:2410.21316v2 Announce Type: replace-cross Abstract: Transformers and large language models~(LLMs) have seen rapid adoption in all domains. Their sizes have exploded to hundreds of billions of pa

hardwarearxiv-cs-ai

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Detecting Corporate AI-Washing via Cross-Modal Semantic Inconsistency Learning

DGX agent

arXiv:2604.09644v1 Announce Type: cross Abstract: Corporate AI-washing-the strategic misrepresentation of AI capabilities via exaggerated or fabricated cross-channel disclosures-has emerged as a syste

model-releasesarxiv-cs-ai

14 Apr 2026

Device-Conditioned Neural Architecture Search for Efficient Robotic Manipulation

arXiv:2604.10170v1 Announce Type: cross Abstract: The growing complexity of visuomotor policies poses significant challenges for deployment with heterogeneous robotic hardware constraints. However, mo

Dialogue based Interactive Explanations for Safety Decisions in Human Robot Collaboration

arXiv:2604.05896v2 Announce Type: replace Abstract: As robots increasingly operate in shared, safety critical environments, acting safely is no longer sufficient robots must also make their safety dec

safetyarxiv-cs-ro

Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky

arXiv:2507.03336v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly tasked with invoking enterprise APIs, yet they routinely falter when near-duplicate tools vie for the

Efficient Personalization of Generative User Interfaces

arXiv:2604.09876v1 Announce Type: cross Abstract: Generative user interfaces (UIs) create new opportunities to adapt interfaces to individual users on demand, but personalization remains difficult bec

researcharxiv-cs-ai

Eliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach

model-releasesarxiv-cs-cl

arXiv:2604.11547v1 Announce Type: cross Abstract: While large language models hold promise for complex medical applications, their development is hindered by the scarcity of high-quality reasoning dat

Enhancing Fine-Grained Spatial Grounding in 3D CT Report Generation via Discriminative Guidance

arXiv:2604.10437v1 Announce Type: new Abstract: Vision--language models (VLMs) for radiology report generation (RRG) can produce long-form chest CT reports from volumetric scans and show strong potent

From Topology to Trajectory: LLM-Driven World Models For Supply Chain Resilience

arXiv:2604.11041v1 Announce Type: new Abstract: Semiconductor supply chains face unprecedented resilience challenges amidst global geopolitical turbulence. Conventional Large Language Model (LLM) plan

Governed Reasoning for Institutional AI

arXiv:2604.10658v1 Announce Type: new Abstract: Institutional decisions -- regulatory compliance, clinical triage, prior authorization appeal -- require a different AI architecture than general-purpos

GraspSense: Physically Grounded Grasp and Grip Planning for a Dexterous Robotic Hand via Language-Guided Perception and Force Maps

arXiv:2604.05697v2 Announce Type: replace Abstract: Dexterous robotic manipulation requires more than geometrically valid grasps: it demands physically grounded contact strategies that account for the

local-aiarxiv-cs-ro

Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models

arXiv:2604.09687v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel on many multimodal reasoning benchmarks, but these evaluations often do not require an exhaustive readout of the i

GTASA: Ground Truth Annotations for Spatiotemporal Analysis, Evaluation and Training of Video Models

arXiv:2604.10385v1 Announce Type: new Abstract: Generating complex multi-actor scenario videos remains difficult even for state-of-the-art neural generators, while evaluating them is hard due to the l

Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution

arXiv:2604.10271v1 Announce Type: cross Abstract: In what way could a data breach involving government-issued IDs such as passports, driver's licenses, etc., rival a random voluntary disclosure on a n

researcharxiv-cs-cl

HyperGraphPro: Progress-Aware Reinforcement Learning for Structure-Guided Hypergraph RAG

arXiv:2601.17755v2 Announce Type: replace Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has emerged as a promising paradigm that organizes external knowledge into structured graphs of enti

safetyarxiv-cs-cl

IceCache: Memory-efficient KV-cache Management for Long-Sequence LLMs

arXiv:2604.10539v1 Announce Type: cross Abstract: Key-Value (KV) cache plays a crucial role in accelerating inference in large language models (LLMs) by storing intermediate attention states and avoid

hardwarearxiv-cs-ai

Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part III -- Gradient Descent, Neural Plasticity, and the Emergence of Deep Intelligence

arXiv:2604.09677v1 Announce Type: cross Abstract: In Parts I and II of this series, we established isomorphisms between ant colony decision-making and two major families of ensemble learning: random f

LABBench2: An Improved Benchmark for AI Systems Performing Biology Research

arXiv:2604.09554v1 Announce Type: new Abstract: Optimism for accelerating scientific discovery with AI continues to grow. Current applications of AI in scientific research range from training dedicate

LaMI: Augmenting Large Language Models via Late Multi-Image Fusion

model-releasesarxiv-cs-cl

arXiv:2406.13621v2 Announce Type: replace Abstract: Commonsense reasoning often requires both textual and visual knowledge, yet Large Language Models (LLMs) trained solely on text lack visual groundin

Large Language Model as An Operator: An Experience-Driven Solution for Distribution Network Voltage Control

arXiv:2507.14800v2 Announce Type: replace-cross Abstract: With the advanced reasoning, contextual understanding, and information synthesis capabilities of large language models (LLMs), a novel paradig

Learning Hierarchical and Geometry-Aware Graph Representations for Text-to-CAD

arXiv:2604.10075v1 Announce Type: new Abstract: Text-to-CAD code generation is a long-horizon task that translates textual instructions into long sequences of interdependent operations. Existing metho

local-aiarxiv-cs-ai

Learning When Not to Learn: Risk-Sensitive Abstention in Bandits with Unbounded Rewards

arXiv:2510.14884v3 Announce Type: replace-cross Abstract: In high-stakes AI applications, even a single action can cause irreparable damage. However, nearly all of sequential decision-making theory as

MDP Planning as Policy Inference

arXiv:2602.17375v2 Announce Type: replace Abstract: We cast episodic Markov decision process (MDP) planning as Bayesian inference over policies. A policy is treated as the latent variable and is assig

Mixture of Cognitive Reasoners: Modular Reasoning with Brain-Like Specialization

arXiv:2506.13331v3 Announce Type: replace Abstract: Human cognitive behavior arises from the interaction of specialized brain networks dedicated to distinct functions, such as language, logic, and soc

Multi-Granularity Reasoning for Image Quality Assessment via Attribute-Aware Reinforcement Learning to Rank

arXiv:2604.09704v1 Announce Type: new Abstract: Recent advances in reasoning-induced image quality assessment (IQA) have demonstrated the power of reinforcement learning to rank (RL2R) for training vi

Tutorials

Multimodal Diffusion Forcing for Forceful Manipulation

arXiv:2511.04812v2 Announce Type: replace-cross Abstract: Given a dataset of expert trajectories, standard imitation learning approaches typically learn a direct mapping from observations (e.g., RGB i

tutorialsarxiv-cs-ai

NameBERT: Scaling Name-Based Nationality Classification with LLM-Augmented Open Academic Data

arXiv:2604.10401v1 Announce Type: new Abstract: Inferring nationality from personal names is a critical capability for equity and bias monitoring, personalization, and a valuable tool in biomedical an

safetyarxiv-cs-cl

Network Effects and Agreement Drift in LLM Debates

arXiv:2604.11312v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated an unprecedented ability to simulate human-like social behaviors, making them useful tools for simulati

researcharxiv-cs-ai

Tutorials

Not Your Stereo-Typical Estimator: Combining Vision and Language for Volume Perception

arXiv:2604.09886v1 Announce Type: cross Abstract: Accurate volume estimation of objects from visual data is a long-standing challenge in computer vision with significant applications in robotics, logi

tutorialsarxiv-cs-ai

PRISM Risk Signal Framework: Hierarchy-Based Red Lines for AI Behavioral Risk

arXiv:2604.11070v1 Announce Type: new Abstract: Current approaches to AI safety define red lines at the case level: specific prompts, specific outputs, specific harms. This paper argues that red lines

Prompt Injection as Role Confusion

arXiv:2603.12277v3 Announce Type: replace-cross Abstract: Language models remain vulnerable to prompt injection attacks despite extensive safety training. We trace this failure to role confusion: mode

Prompt Relay: Inference-Time Temporal Control for Multi-Event Video Generation

arXiv:2604.10030v1 Announce Type: new Abstract: Video diffusion models have achieved remarkable progress in generating high-quality videos. However, these models struggle to represent the temporal suc

Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers

arXiv:2505.04842v2 Announce Type: replace-cross Abstract: Prevalent reinforcement learning~(RL) methods for fine-tuning LLM reasoners, such as GRPO or Leave-one-out PPO, abandon the learned value func

researcharxiv-cs-ai

Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid

arXiv:2511.04776v2 Announce Type: replace-cross Abstract: Generative Artificial Intelligence (GenAI) represents a rapidly expanding digital infrastructure whose energy demand and associated CO2 emissi

safetyarxiv-cs-cl

ReContraster: Making Your Posters Stand Out with Regional Contrast

model-releasesarxiv-cs-cv

arXiv:2604.10442v1 Announce Type: new Abstract: Effective poster design requires rapidly capturing attention and clearly conveying messages. Inspired by the ``contrast effects'' principle, we propose

Regularized Entropy Information Adaptation with Temporal-Awareness Networks for Simultaneous Speech Translation

arXiv:2604.09916v1 Announce Type: new Abstract: Simultaneous Speech Translation (SimulST) requires balancing high translation quality with low latency. Recent work introduced REINA, a method that trai

Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale

model-releasesarxiv-cs-cl

arXiv:2604.11554v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training has proven effective at unlocking reasoning, self-reflection, and tool-use capabilities in large language mode

RL-Driven Sustainable Land-Use Allocation for the Lake Malawi Basin

arXiv:2604.03768v2 Announce Type: replace Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This pap

SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding

arXiv:2604.09557v1 Announce Type: cross Abstract: Speculative Decoding (SD) has emerged as a critical technique for accelerating Large Language Model (LLM) inference. Unlike deterministic system optim

SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting

arXiv:2407.20799v3 Announce Type: replace Abstract: Facial expression spotting, identifying periods where facial expressions occur in a video, is a significant yet challenging task in facial expressio

local-aiarxiv-cs-cv

StreamServe: Adaptive Speculative Flows for Low-Latency Disaggregated LLM Serving

arXiv:2604.09562v1 Announce Type: cross Abstract: Efficient LLM serving must balance throughput and latency across diverse, bursty workloads. We introduce StreamServe, a disaggregated prefill decode s

hardwarearxiv-cs-ai

Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes

arXiv:2604.10371v1 Announce Type: new Abstract: This study proposes Structural Gating and Effect-aligned Discovery for Temporal Causal Discovery (SGED-TCD), a novel and general framework for lag-resol

SVD-Prune: Training-Free Token Pruning For Efficient Vision-Language Models

arXiv:2604.11530v1 Announce Type: cross Abstract: Vision-Language Models (VLM) have revolutionized multimodal learning by jointly processing visual and textual information. Yet, they face significant

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604.10180v1 Announce Type: cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existin

hardwarearxiv-cs-lg

THOM: Generating Physically Plausible Hand-Object Meshes From Text

arXiv:2604.02736v3 Announce Type: replace Abstract: Generating photorealistic 3D hand-object interactions (HOIs) from text is important for applications like robotic grasping and AR/VR content creatio

Towards Near-Real-Time Telemetry-Aware Routing with Neural Routing Algorithms

arXiv:2604.02927v2 Announce Type: replace Abstract: Routing algorithms are crucial for efficient computer network operations, and in many settings they must be able to react to traffic bursts within m

local-aiarxiv-cs-lg

VLMaterial: Vision-Language Model-Based Camera-Radar Fusion for Physics-Grounded Material Identification

arXiv:2604.11671v1 Announce Type: cross Abstract: Accurate material recognition is a fundamental capability for intelligent perception systems to interact safely and effectively with the physical worl

safetyarxiv-cs-ro

Warm-Started Reinforcement Learning for Iterative 3D/2D Liver Registration

arXiv:2604.10245v1 Announce Type: new Abstract: Registration between preoperative CT and intraoperative laparoscopic video plays a crucial role in augmented reality (AR) guidance for minimally invasiv