Search: “models”

MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference

arXiv:2605.05225v2 Announce Type: replace-cross Abstract: Mixture-of-Experts Multimodal Large Language Models (MoE MLLMs) suffer from a significant efficiency bottleneck during Expert Parallelism (EP)

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MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems

DGX agent

arXiv:2605.06623v1 Announce Type: cross Abstract: Large language model (LLM)-based Multi-agent systems (MAS) have shown promise in tackling complex collaborative tasks, where agents are typically orch

agentsarxiv-cs-lg

11 May 2026

Agents

MedExAgent: Training LLM Agents to Ask, Examine, and Diagnose in Noisy Clinical Environments

arXiv:2605.07058v1 Announce Type: cross Abstract: Real-world clinical diagnosis is a complex process in which the doctor is required to obtain information from both interaction with the patient and co

agentsarxiv-cs-ai

MIST: Multimodal Interactive Speech-based Tool-calling Conversational Assistants for Smart Homes

arXiv:2605.06897v1 Announce Type: cross Abstract: The rise of Internet of Things (IoT) devices in the physical world necessitates voice-based interfaces capable of handling complex user experiences. W

applicationsarxiv-cs-ai

MoCoTalk: Multi-Conditional Diffusion with Adaptive Router for Controllable Talking Head Generation

arXiv:2605.08050v1 Announce Type: new Abstract: Talking-head generation requires joint modeling of identity, head pose, facial expression, and mouth dynamics. Existing methods typically address only a

safetyarxiv-cs-cv

Tutorials

Not All Tokens Learn Alike: Attention Entropy Reveals Heterogeneous Signals in RL Reasoning

arXiv:2605.07660v1 Announce Type: new Abstract: Reinforcement-learning-based post-training has become a key approach for improving the reasoning ability of large language models, but its token-level l

tutorialsarxiv-cs-cl

Not All Tokens Need 40 Steps: Heterogeneous Step Allocation in Diffusion Transformers for Efficient Video Generation

arXiv:2605.06892v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have achieved state-of-the-art video generation quality, but they incur immense computational cost because standard infere

researcharxiv-cs-cv

OASES: Outcome-Aligned Search-Evaluation Co-Training for Agentic Search

arXiv:2604.03675v2 Announce Type: replace Abstract: Agentic search enables language models to solve knowledge-intensive tasks by adaptively acquiring external evidence over multiple steps. Reinforceme

OneViewAll: Semantic Prior Guided One-View 6D Pose Estimation for Novel Objects

arXiv:2605.07023v1 Announce Type: new Abstract: In many practical 6D object pose estimation scenarios, we often have access to only a single real-world RGB-D reference view per object, typically witho

applicationsarxiv-cs-cv

Online Allocation with Unknown Shared Supply

arXiv:2605.07080v1 Announce Type: new Abstract: Many real-world resource allocation systems, such as humanitarian logistics and vaccine distribution, must preposition limited supply across multiple lo

Online Localized Conformal Prediction

arXiv:2605.05497v2 Announce Type: replace Abstract: Conformal prediction is a framework that provides valid uncertainty quantification for general models with exchangeable data. However, in the online

Physics-Based Benchmarking Metrics for Multimodal Synthetic Images

arXiv:2511.15204v3 Announce Type: replace-cross Abstract: Current state of the art measures like BLEU, CIDEr, VQA score, SigLIP-2 and CLIPScore are often unable to capture semantic or structural accur

Physics-Informed Reduced-Order Operator Learning for Hyperelasticity in Continuum Micromechanics

arXiv:2605.07738v1 Announce Type: cross Abstract: Physics-informed operator learning is an attractive candidate for surrogate modeling of microstructures, especially in multiscale finite-element simul

POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles

arXiv:2605.07775v1 Announce Type: cross Abstract: Balancing exploration and exploitation is a core challenge in sequential decision-making and black-box optimization. We introduce POETS (extbf{Po}licy

Prune-OPD: Efficient and Reliable On-Policy Distillation for Long-Horizon Reasoning

arXiv:2605.07804v1 Announce Type: cross Abstract: On-policy distillation (OPD) leverages dense teacher rewards to enhance reasoning models. However, scaling OPD to long-horizon tasks exposes a critica

Rebalancing gradient to improve self-supervised co-training of depth, odometry and optical flow predictions

arXiv:2605.07945v1 Announce Type: new Abstract: We present CoopNet, an approach that improves the cooperation of co-trained networks by dynamically adapting the apportionment of gradient, to ensure eq

researcharxiv-cs-cv

ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

arXiv:2408.06747v4 Announce Type: replace Abstract: Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. Ho

safetyarxiv-cs-cv

Repeated Deceptive Path Planning against Learnable Observer

arXiv:2605.07174v1 Announce Type: new Abstract: We study the problem of deceptive path planning (DPP), where an agent aims to conceal its true destination from external observers. While existing work

Retrieve, Integrate, and Synthesize: Spatial-Semantic Grounded Latent Visual Reasoning

arXiv:2605.07106v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have made remarkable progress on vision-language reasoning, yet most methods still compress visual evidence int

researcharxiv-cs-cl

Rubric-based On-policy Distillation

arXiv:2605.07396v1 Announce Type: cross Abstract: On-policy distillation (OPD) is a powerful paradigm for model alignment, yet its reliance on teacher logits restricts its application to white-box sce

Agents

See Tomorrow, Act Today: Foresight-Driven Autonomous Driving

arXiv:2605.07195v1 Announce Type: new Abstract: Current end-to-end autonomous driving planners are fundamentally reactive: they condition on historical and present observations to predict future actio

agentsarxiv-cs-cv

Semantic-Aware Adaptive Visual Memory for Streaming Video Understanding

arXiv:2605.07897v1 Announce Type: cross Abstract: Online streaming video understanding requires models to process continuous visual inputs and respond to user queries in real time, where the unbounded

hardwarearxiv-cs-ai

Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning

arXiv:2605.06130v2 Announce Type: replace Abstract: A persistent skill library allows language model agents to reuse successful strategies across tasks. Maintaining such a library requires three coupl

Slowly Annealed Langevin Dynamics: Theory and Applications to Training-Free Guided Generation

arXiv:2605.07950v1 Announce Type: new Abstract: We study Slowly Annealed Langevin Dynamics (SALD), a sampler for tracking a path of moving target distributions and approximating the terminal target th

safetyarxiv-cs-lg

SOCKET: SOft Collision Kernel EsTimator for Sparse Attention

arXiv:2602.06283v2 Announce Type: replace Abstract: Exploiting sparsity during long-context inference is key to scaling large language models, as attention dominates the cost of autoregressive decodin

hardwarearxiv-cs-lg

Sparse Autoencoders as Plug-and-Play Firewalls for Adversarial Attack Detection in VLMs

arXiv:2605.07447v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced rapidly and are increasingly deployed in real-world applications, especially with the rise of agent-based

SparseRL-Sync: Lossless Weight Synchronization with ~100x Less Communication

arXiv:2605.07330v1 Announce Type: cross Abstract: In large-scale reinforcement learning (RL) systems with decoupled Trainer-Rollout execution, the Trainer must regularly synchronize policy weights to

The Moltbook Files: A Harmless Slopocalypse or Humanity's Last Experiment

arXiv:2605.07462v1 Announce Type: cross Abstract: Moltbook is a Reddit-like platform where OpenClaw agents post, comment, and vote at scale - a so far unprecedented incident that comes with serious sa

TopoPrune: Robust Data Pruning via Unified Latent Space Topology

arXiv:2602.02739v2 Announce Type: replace-cross Abstract: Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geom

Towards an Inferentialist Account of Information Through Proof-theoretic Semantics

arXiv:2605.05368v2 Announce Type: replace-cross Abstract: Information is one of the most widely-discussed concepts of the current era. However, a great deal of insightful work notwithstanding, it is y

Uncertainty Quantification for Prior-Data Fitted Networks using Martingale Posteriors

arXiv:2505.11325v4 Announce Type: replace-cross Abstract: Prior-data fitted networks (PFNs) have emerged as promising foundation models for prediction from tabular datasets, achieving state-of-the-art

applicationsarxiv-cs-ai

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding

arXiv:2605.05848v2 Announce Type: replace-cross Abstract: Video large multimodal models increasingly face a scalability bottleneck: long videos produce excessively long visual-token sequences, which s

VIMCAN: Visual-Inertial 3D Human Pose Estimation with Hybrid Mamba-Cross-Attention Network

arXiv:2605.07552v1 Announce Type: new Abstract: The rapid advances in deep learning have significantly enhanced the accuracy of multimodal 3D human pose estimation (HPE). However, the state-of-the-art

researcharxiv-cs-cv

VNN-LIB 2.0: Rigorous Foundations for Neural Network Verification

arXiv:2605.07451v1 Announce Type: new Abstract: Neural network verification is an active and rapidly maturing research area, with a growing ecosystem of solvers and tools. The VNN-LIB standard was int

WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation

arXiv:2605.07522v1 Announce Type: new Abstract: Accurate weather forecast reporting enables individuals and communities to better plan daily activities and agricultural operations. However, the curren

researcharxiv-cs-cl

Local Ai

3D Ultrasound-Derived Pseudo-CT Synthesis Using a Transformer-Augmented Residual Network for Real-Time Operator Guidance

arXiv:2605.04856v1 Announce Type: new Abstract: Computed tomography (CT) is indispensable for clinical diagnosis and image-guided interventions but exposes patients to ionizing radiation, motivating t

local-aiarxiv-cs-cv

A Hybrid Method for Low-Resource Named Entity Recognition

arXiv:2605.04489v1 Announce Type: cross Abstract: Named Entity Recognition (NER) is a critical component of Natural Language Processing with diverse applications in information extraction and conversa

applicationsarxiv-cs-cl

A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints

arXiv:2605.04595v1 Announce Type: new Abstract: The rapid adoption of large language models (LLMs) has created significant challenges for efficient inference at scale. Unlike traditional workloads, LL

hardwarearxiv-cs-lg

Active Contact Sensing for Robust Robot-to-Human Object Handover

arXiv:2605.04610v1 Announce Type: new Abstract: Robot-to-human object handover is an essential skill for robot assistants, from serving drinks at home to passing surgical tools in the operating room.

researcharxiv-cs-ro

Adaptive Consensus in LLM Ensembles via Sequential Evidence Accumulation: Automatic Budget Identification and Calibrated Commit Signals

arXiv:2605.04236v1 Announce Type: new Abstract: Large Language Model ensembles improve reasoning accuracy up to a performance boundary; beyond it, additional deliberation degrades accuracy. Static-bud

Local Ai

Adaptive Learning Strategies for AoA-Based Outdoor Localization: A Comprehensive Framework

arXiv:2605.05055v1 Announce Type: new Abstract: Localization in 5G and 6G networks is essential for important use cases such as intelligent transportation, smart factories, and smart cities. Although

local-aiarxiv-cs-lg

Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks

arXiv:2309.09550v4 Announce Type: replace-cross Abstract: The human brain can self-organize rich and diverse sparse neural pathways to incrementally master hundreds of cognitive tasks. However, most e

Advancing Analytic Class-Incremental Learning through Vision-Language Calibration

arXiv:2602.13670v2 Announce Type: replace Abstract: Class-incremental learning (CIL) with pre-trained models (PTMs) faces a critical trade-off between efficient adaptation and long-term stability. Whi

safetyarxiv-cs-lg

Anatomy of a failure: When, how, and why deep vision fails in scientific domains

arXiv:2605.04231v1 Announce Type: new Abstract: Mirroring its ubiquity in popular media and all human activities, the use of deep learning (DL) is rapidly growing in scientific imaging modalities. How

safetyarxiv-cs-cv

Local Ai

ARISE: A Repository-level Graph Representation and Toolset for Agentic Fault Localization and Program Repair

arXiv:2605.03117v1 Announce Type: cross Abstract: Repository-level fault localization (FL) and automated program repair (APR) require an agent to identify the relevant code units across files, follow

local-aiarxiv-cs-ai

Beyond Variance: Prompt-Efficient RLVR via Rare-Event Amplification and Bidirectional Pairing

arXiv:2602.03452v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) is effective for training large language models on deterministic outcome reasoning tasks. Prio

Budget-aware Auto Optimizer Configurator

arXiv:2605.04711v1 Announce Type: cross Abstract: Optimizer states occupy massive GPU memory in large-scale model training. However, gradients in different network blocks exhibit distinct behaviors, s

hardwarearxiv-cs-lg

Copula-Based Endogeneity Correction for Doubly Robust Estimation of Treatment Effect

arXiv:2605.03278v2 Announce Type: cross Abstract: Doubly Robust (DR) estimation of treatment effect relies on an untestable assumption that is the absence of unobserved confounding. This assumption is