Search: “framework”

Prescribe-then-Select: Adaptive Policy Selection for Contextual Stochastic Optimization

model-releasesarxiv-cs-lg

arXiv:2509.08194v2 Announce Type: replace Abstract: We address the problem of policy selection in contextual stochastic optimization (CSO), where covariates are available as contextual information and

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Prioritize the Process, Not Just the Outcome: Rewarding Latent Thought Trajectories Improves Reasoning in Looped Language Models

DGX agent

arXiv:2602.10520v3 Announce Type: replace Abstract: Looped Language Models (LoopLMs) perform multi-step latent reasoning prior to token generation and outperform conventional LLMs on reasoning benchma

model-releasesarxiv-cs-lg

29 May 2026

PRO-CUA: Process-Reward Optimization for Computer Use Agents

arXiv:2605.29119v1 Announce Type: new Abstract: Computer use agents (CUAs) have shown strong potential for automating complex digital workflows, yet their training remains constrained by costly live e

Projectional Decoding: Towards Semantic-Aware LLM Generation

arXiv:2605.30054v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate software artifacts across many software engineering (SE) tasks, yet ensuring the semant

researcharxiv-cs-ai

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation

arXiv:2310.14161v2 Announce Type: replace Abstract: Machine learning has been successfully applied to improve the efficiency of Mixed-Integer Linear Programming (MILP) solvers. However, the learning-b

Pushing the Limits of Block Rotations in Post-Training Quantization

arXiv:2601.22347v2 Announce Type: replace-cross Abstract: Recent post-training quantization (PTQ) methods have adopted block rotations to diffuse outliers prior to rounding. While this reduces the ove

researcharxiv-cs-ai

Quantum-Enhanced Adversarial Robustness in Artificial Intelligence

arXiv:2605.28899v1 Announce Type: cross Abstract: Artificial Intelligence has achieved remarkable success across diverse application domains. However, its vulnerability to adversarial attacks poses si

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

arXiv:2605.30280v1 Announce Type: cross Abstract: Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented cap

RAISE: RAG Design as an Architecture Search Problem

arXiv:2605.30029v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems expose numerous design choices spanning query rewriting, chunking, retrieval depth, reranking, and context

Rare Event Analysis of Large Language Models

arXiv:2602.06791v2 Announce Type: replace Abstract: Being probabilistic models, during inference large language models (LLMs) display rare events: behaviour that is far from typical but highly signifi

researcharxiv-cs-lg

Real-Time Retargeting Using Controllability Boundary for Chandrayaan-3 Lunar Landing

arXiv:2605.29412v1 Announce Type: cross Abstract: This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates a

ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2605.29114v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models with integrated reasoning have been proposed for end-to-end autonomous driving, assuming a tight coupling between

Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning

arXiv:2602.00994v2 Announce Type: replace Abstract: Agentic Reinforcement Learning (ARL) trains large language models to interleave reasoning with external tool execution to solve complex tasks. Most

Tutorials

Reasoning that Travels: Dissecting How Chain-of-Thought Transfers Across Models

arXiv:2605.28913v1 Announce Type: new Abstract: Large reasoning models (LRMs) often generate extensive chain-of-thought (CoT) traces before producing a final answer. As explicit textual artifacts, the

tutorialsarxiv-cs-cl

Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents

arXiv:2605.29447v1 Announce Type: cross Abstract: While GUI agents have advanced rapidly, they often lack the robustness to recover from their own errors, hindering real-world deployment. To bridge th

safetyarxiv-cs-cl

Reinforcing Few-step Generators via Reward-Tilted Distribution Matching

arXiv:2605.26108v2 Announce Type: replace Abstract: Recent advances in few-step diffusion distillation have enabled efficient image generation, yet aligning these models with human preferences remains

safetyarxiv-cs-cv

Replicable Simulation-Based Robot Validation through Provenance

arXiv:2605.29973v1 Announce Type: new Abstract: Robot behavior is often validated through simulation-based testing, yet the replicability of such campaigns depends critically on transparent documentat

safetyarxiv-cs-ro

Representation Unlearning: Forgetting through Information Compression

model-releasesarxiv-cs-lg

arXiv:2601.21564v2 Announce Type: replace Abstract: Machine unlearning seeks to remove the influence of specific training data from a model, a need driven by privacy regulations and robustness concern

REST3D: Reconstructing Physically Stable 3D Scenes from a Single Image

arXiv:2605.30338v1 Announce Type: new Abstract: Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applic

safetyarxiv-cs-cv

Rethinking Stepwise Model Routing: A Cost-Efficient Table Reasoning Perspective

arXiv:2605.29319v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on table reasoning tasks but incur substantial inference cost due to long reasoning traces. Ste

researcharxiv-cs-cl

Return-to-Go Is More Than a Number: Q-Guided Alignment for Return-Conditioned Supervised Learning

arXiv:2605.29028v1 Announce Type: cross Abstract: Conditioned Sequence Models (CSMs) learn policies by treating return-to-go (RTG) as a control signal. However, existing CSMs often treat the RTGs as s

RoboWits: Unexpected Challenges for Robotic Creative Problem Solving

arXiv:2605.30326v1 Announce Type: cross Abstract: The ability to reason, adapt, and creatively solve problems under unexpected challenges is essential for robots operating in real-world environments.

Robust and Generalizable Safety Steering for Text-to-Image Diffusion Transformers

arXiv:2605.30049v1 Announce Type: new Abstract: Diffusion Transformers have become a powerful backbone for text-to-image generation, but their layered and cross-modal generation process makes safety c

Tutorials

Robust Cross-Domain Generalization Using Unlabeled Target Data with Source-Domain Supervision

arXiv:2605.29122v1 Announce Type: new Abstract: It is often desirable to generalize medical imaging AI models trained with dense annotations to data acquired from different ultrasound scanners or clin

tutorialsarxiv-cs-cv

Robust Frequency-Calibrated Virtual EEG Channel Generation from Four Frontal Electrodes for Wearable EEG Augmentation

arXiv:2605.29263v1 Announce Type: new Abstract: Low-channel wearable electroencephalography (EEG) is attractive for long-term monitoring, but four frontal electrodes provide only a sparse and spatiall

researcharxiv-cs-lg

RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains

arXiv:2605.29156v1 Announce Type: cross Abstract: Pointwise reward modeling offers critical signals for LLM post-training, yet struggles with absolute scoring in subjective, non-verifiable settings. R

safetyarxiv-cs-cl

Rubric-Guided Process Reward for Stepwise Model Routing

arXiv:2605.29310v1 Announce Type: new Abstract: Stepwise model routing improves the efficiency of Large Reasoning Models (LRMs) by assigning each reasoning step to a suitable model. Recent methods for

Hardware

Run Step 3.7 Flash on NVIDIA GPUs with Enterprise-Ready Multimodal AI

Step 3.7 Flash is a 198B-parameter Mixture-of-Experts vision-language model designed for enterprise-scale production workloads, featuring native image and video input, a 256k context window, and confi

hardwarenvidia-developer

S-MARC: Causal Streaming Reasoning for Full-Duplex Conversational Behavior Modeling

arXiv:2602.11065v2 Announce Type: replace-cross Abstract: Human conversation is organized by an implicit chain of thought and manifests as temporally structured conversational behaviors. Capturing thi

Local Ai

S3Mem: Structured Spatiotemporal Scene-Event Memory for Long-Horizon Interactive Question Answering

arXiv:2605.28831v1 Announce Type: cross Abstract: Long-horizon interactive agents often accumulate large trajectory histories yet still fail to answer questions about earlier events reliably. We argue

local-aiarxiv-cs-ai

SAAS: Self-Aware Reinforcement Learning for Over-Search Mitigation in Agentic Search

arXiv:2605.29796v1 Announce Type: new Abstract: Agentic search enables LLMs to solve complex multi-hop questions through iterative reasoning and external search. Despite the effectiveness, these syste

Applications

SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation

arXiv:2605.29662v1 Announce Type: new Abstract: Real-time inference of vision-language-action (VLA) models is essential for robotic control. While visual token pruning has shown strong potential for a

applicationsarxiv-cs-cv

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents

arXiv:2509.23694v5 Announce Type: replace Abstract: Search agents connect LLMs to the Internet, enabling them to access broader and more up-to-date information. However, this also introduces a new thr

SAGE: Segment-Aware Gloss-Free Encoding for Token-Efficient Sign Language Translation

model-releasesarxiv-cs-cv

arXiv:2507.09266v2 Announce Type: replace Abstract: Gloss-free Sign Language Translation (SLT) has advanced rapidly, achieving strong performances without relying on gloss annotations. However, these

Applications

SAM3D-Phys: Towards Multi-Object Interactive Simulation in Real World

arXiv:2605.30239v1 Announce Type: new Abstract: This work addresses the problem of recovering complete, simulatable object geometry from reconstructed real-world scenes, enabling physics-based interac

applicationsarxiv-cs-cv

Same Question, Different Source, Different Answer: Auditing Source-Dependence in Medical Multi-Source RAG

arXiv:2605.29084v1 Announce Type: cross Abstract: A retrieval-augmented generation (RAG) system deployed over a multi-author institutional corpus can give a different answer to the same question depen

SAVAA: Mitigating Hallucinations in LVLMs via Step-wise Adaptive Visual Attention Amplification

arXiv:2602.13600v2 Announce Type: replace Abstract: A line of recent training-free methods for mitigating hallucinations in large vision-language models (LVLMs) operates by amplifying attention to vis

researcharxiv-cs-cv

Applications

Scalable RF Simulation in Generative 4D Worlds

arXiv:2508.12176v2 Announce Type: replace-cross Abstract: Radio Frequency (RF) sensing has emerged as a powerful, privacy-preserving alternative to vision-based methods for various perception tasks. H

applicationsarxiv-cs-ai

Agents

Scaling Small Agents Through Strategy Auctions

arXiv:2602.02751v2 Announce Type: replace-cross Abstract: Small language models are increasingly viewed as a promising, cost-effective approach to agentic AI, with proponents claiming they are suffici

agentsarxiv-cs-ai

Hardware

ScheduleStream: Temporal Planning with Samplers for GPU-Accelerated Multi-Arm Task and Motion Planning & Scheduling

arXiv:2511.04758v2 Announce Type: replace-cross Abstract: Bimanual and humanoid robots are appealing because of their human-like ability to leverage multiple arms to efficiently complete tasks. Howeve

hardwarearxiv-cs-ai

SCoOP: Semantic Consistent Opinion Pooling for Uncertainty Quantification in Multiple Vision-Language Model Systems

arXiv:2603.23853v3 Announce Type: replace Abstract: Combining multiple Vision-Language Models (VLMs) can enhance multimodal reasoning and robustness, but aggregating heterogeneous models' outputs ampl

researcharxiv-cs-ai

Securing SIM-Assisted Wireless Networks via Quantum Reinforcement Learning

arXiv:2602.13238v2 Announce Type: replace-cross Abstract: Stacked intelligent metasurfaces (SIMs) have recently emerged as a powerful wave-domain technology that enables multi-stage manipulation of el

Tutorials

Seeing through boxes: Non-Line-of-Sight 3D Reconstruction from Radar Signals

arXiv:2605.29098v1 Announce Type: new Abstract: Reconstructing object geometry from radio frequency (RF) signals is fundamentally challenging due to the lensless imaging nature of RF sensing, which le

tutorialsarxiv-cs-cv

Self-Play Reinforcement Learning under Imperfect Information in Big 2

arXiv:2605.28863v1 Announce Type: cross Abstract: Imperfect-information multiplayer games test whether agents can act under hidden information, sparse rewards, and non-stationary opponents. We study t

Semantic and Visual Evidence for Efficient Long-Video Reasoning: A Solution for the HD-EPIC VQA Challenge

arXiv:2605.29402v1 Announce Type: cross Abstract: Understanding long-form egocentric videos remains challenging for multimodal large language models (MLLMs) due to limited context length and insuffici

SERC: LDPC-Inspired Semantic Error Correction for Retrieval-Augmented Generation

arXiv:2605.28837v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated remarkable capabilities, their reliability is significantly compromised by hallucinations. Existi

SigmaMedStat: Temporal Signal Modeling for ICU False Alarm Reduction

arXiv:2605.29236v1 Announce Type: new Abstract: Alarm fatigue in intensive care units (ICUs) is a well documented patient safety crisis. Clinical monitors generate 350 or more alarms per patient per d

Skill-Pro: Learning Reusable Skills from Experience via Non-Parametric PPO for LLM Agents

arXiv:2602.01869v3 Announce Type: replace Abstract: LLM-driven agents excel at sequential decision-making but often rely on on-the-fly reasoning, re-deriving solutions even in recurring scenarios. Thi