Search: “inference”

Linear Scaling Video VLMs for Long Video Understanding

arXiv:2605.31598v1 Announce Type: new Abstract: Video vision-language models (VLMs) are increasingly used in long-horizon and streaming settings, yet most video encoders still rely on spatiotemporal s

researcharxiv-cs-cv

LLM Anonymization Against Agentic Re-Identificatio

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DGX agent

arXiv:2605.30848v1 Announce Type: cross Abstract: Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become cross-referenceable evidence for re-ident

agentsarxiv-cs-cl

1 Jun 2026

Local Ai

LocalSUG: City-Preference-Enhanced LLM for Query Suggestion in Local-Life Services

arXiv:2603.04946v2 Announce Type: replace Abstract: In local-life service platforms, query suggestion reduces user effort by generating candidate queries from input prefixes. Traditional multi-stage s

local-aiarxiv-cs-cl

MADS: Model-Aware Diverse Core Set Selection for Instruction Tuning

arXiv:2605.30857v1 Announce Type: new Abstract: Instruction fine-tuning is employed to enhance the instruction-following ability of large language models (LLMs). As the amount of instruction fine-tuni

MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts

arXiv:2509.12440v3 Announce Type: replace-cross Abstract: Deploying Large Language Models (LLMs) in medical applications requires fact-checking capabilities to ensure patient safety and regulatory com

Mellum2 Technical Report

arXiv:2605.31268v1 Announce Type: new Abstract: We present Mellum 2, an open-weight 12B-parameter Mixture-of-Experts (MoE) language model with 2.5B active parameters per token. Mellum 2 is a general-p

MindVoice: Reconstructing Intelligible Speech from Non-invasive Neural Signals with Pretrained Priors

arXiv:2605.31173v1 Announce Type: cross Abstract: Reconstructing continuous speech from non-invasive neural recordings is a fundamental problem for probing human auditory perception and building safe,

Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments

arXiv:2605.31443v1 Announce Type: cross Abstract: We present a regression-adjustment framework designed for the estimation of longitudinal treatment effects in randomized experiments under static regi

MosaicLeaks:Privacy Risks in Querying-in-the-Open for Deep Research Agents

arXiv:2605.30727v1 Announce Type: new Abstract: Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external q

MultiAct: Text-to-Motion Generation from Composite Text via Tailored Attention Guidance

arXiv:2605.30925v1 Announce Type: new Abstract: Text-to-motion generation has progressed rapidly in recent years, offering an expressive interface for animation and human-computer interaction. However

researcharxiv-cs-cv

Native Hierarchical and Compositional Representations with Subspace Embeddings

arXiv:2508.16687v2 Announce Type: replace Abstract: Traditional embeddings represent datapoints as vectors, which makes similarity easy to compute but limits how well they capture hierarchies and comp

NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs

arXiv:2505.17595v4 Announce Type: replace-cross Abstract: Large language models (LLMs) achieve impressive performance across domains but face significant challenges when deployed on consumer-grade GPU

NGDBench: Towards Neural Graph Data Management

arXiv:2603.05529v2 Announce Type: replace-cross Abstract: Data critical to real-world decision-making is increasingly found within organizations. Such data is heterogeneous, constantly evolving, and o

NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving

arXiv:2605.31116v1 Announce Type: new Abstract: Recent perception-free end-to-end (E2E) autonomous driving methods bypass explicit perception outputs by compressing dense image patch tokens into compa

agentsarxiv-cs-cv

Tutorials

Personalize Your Large Vision-language Models With In-context Prompt Tuning

arXiv:2605.31513v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated strong general multimodal capability and are increasingly deployed in downstream systems. This tr

tutorialsarxiv-cs-cv

Position: Evaluation of ECG Representations Must Be Fixed

arXiv:2602.17531v2 Announce Type: replace-cross Abstract: This position paper argues that current benchmarking practice in 12-lead ECG representation learning must be fixed to ensure progress is relia

Primitive Subspaces Mediate Few-Shot Transfer in VLAs

arXiv:2605.30695v1 Announce Type: new Abstract: Deploying vision-language-action (VLA) policies in industrial environments requires the ability to teach new tasks at low cost, a property current VLAs

safetyarxiv-cs-ro

Applications

PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection

arXiv:2502.12119v4 Announce Type: replace-cross Abstract: Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications

applicationsarxiv-cs-ai

Probing Collision Grounding in Vision-Language Models for Safe Human-Robot Collaboration

arXiv:2605.31196v1 Announce Type: cross Abstract: Safe human--robot collaboration requires more than visual description: a monitor must determine whether the robot body is safely separated, already co

Pull Requests as a Training Signal for Repo-Level Code Editing

arXiv:2602.07457v2 Announce Type: replace-cross Abstract: Repository-level code editing requires models to understand complex dependencies and execute precise multi-file modifications across a large c

agentsarxiv-cs-ai

Rationalize: Shared Semantic Reasoning for Human-AI Alignment

arXiv:2605.30632v1 Announce Type: cross Abstract: We introduce Rationalize, a role-pair framework for shared semantic reasoning between humans and AI models in data-driven sensemaking. Building on ide

safetyarxiv-cs-ai

Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with glioma

arXiv:2603.08385v2 Announce Type: replace-cross Abstract: Brain tumors result in 20 years of lost life on average. Standard therapies induce complex structural changes in the brain that are monitored

researcharxiv-cs-cv

Applications

ReGuLaR: Relation-Grounded Latent Reasoning for Large Vision-Language Models

arXiv:2605.30587v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has significantly improved the reasoning ability of large vision-language models (LVLMs) by verbalizing intermediate re

applicationsarxiv-cs-cv

Tutorials

Remembering by Reconstructing: Domain Incremental Learning With Test-Time Training on Video Streams

arXiv:2605.31108v1 Announce Type: new Abstract: In this work we introduce a novel approach to domain incremental learning, adapting models over time to evolving, non-stationary data. In contrast to ot

tutorialsarxiv-cs-cv

Local Ai

Rethinking Efficient Crack Segmentation with Task-Aligned Structural-Directional Modeling

arXiv:2605.31048v1 Announce Type: new Abstract: Recent crack segmentation methods often follow generic semantic segmentation designs, using stronger backbones, hybrid CNN-Transformer-Mamba encoders, a

local-aiarxiv-cs-cv

Rethinking Sparse Mixture of Experts from a Unified Perspective

arXiv:2503.22996v3 Announce Type: replace Abstract: Sparse Mixture of Experts (SMoE) models scale the capacity of models while maintaining constant computational overhead. SMoE methods fall into two c

researcharxiv-cs-cl

Retriever Portfolios: A Principled Approach to Adaptive RAG

arXiv:2605.31176v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems typically rely on a single retriever and a single set of hyperparameters, despite facing highly heterogeneo

Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens

arXiv:2605.30960v1 Announce Type: new Abstract: Accurate Zeroth-Order (ZO) Hessian estimation is a cornerstone of derivative-free methods, essential for tasks such as bilevel optimization, Bayesian in

Same Patient, Different Words, Different Diagnosis? Evaluating Semantic Stability in Clinical LLMs

arXiv:2605.30646v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in clinical applications. However, their behavior remains highly sensitive to subtle linguistic var

Hardware

SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer

arXiv:2605.30409v1 Announce Type: cross Abstract: Real-time streaming video-to-video editing (V2V) is critical for interactive applications such as live broadcasting and gaming, yet it remains a formi

hardwarearxiv-cs-ai

SAW-Bench: Learning Situated Awareness in the Real World

model-releasesarxiv-cs-cv

arXiv:2602.16682v2 Announce Type: replace Abstract: A core aspect of human perception is situated awareness, the ability to relate ourselves to the surrounding physical environment and reason over pos

SDM-Q: Cost-Aware Staged Decision-Making for Multi-Omics Classification with Deep Q-Learning

arXiv:2605.31014v1 Announce Type: new Abstract: Multi-omics data provide complementary molecular characterizations of disease phenotypes and play an important role in disease diagnosis and subtype cla

Sequential Subspace Noise Injection Prevents Accuracy Collapse in Certified Unlearning

model-releasesarxiv-cs-lg

arXiv:2601.05134v2 Announce Type: replace Abstract: Certified unlearning based on differential privacy offers strong guarantees but remains largely impractical: the noisy fine-tuning approaches propos

Skill is Not One-Size-Fits-All: Model-Aware Skill Alignment for LLM Agents

arXiv:2605.30723v1 Announce Type: new Abstract: LLM agents increasingly retrieve externally curated skills-procedural instructions retrieved at decision time-to improve performance on long-horizon int

safetyarxiv-cs-cl

Softly Constrained Denoisers for Diffusion Models Applied to Partial Differential Equations

arXiv:2512.14980v4 Announce Type: replace Abstract: Diffusion models have become a powerful generative prior for solutions of partial differential equations (PDEs). Existing approaches enforce physica

Stochastic Gradients under Nuisances

arXiv:2508.20326v2 Announce Type: replace-cross Abstract: Stochastic gradient optimization is the dominant learning paradigm for a variety of scenarios, from classical supervised learning to modern se

Surface Constraint Policy for Learning Surface-Constrained and Dynamically Feasible Robot Skills

arXiv:2605.31321v1 Announce Type: new Abstract: Diffusion-based imitation learning methods have driven rapid progress in robot dexterous manipulation tasks. However, they have limitations when applied

safetyarxiv-cs-ro

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection

arXiv:2603.12916v3 Announce Type: replace-cross Abstract: Multivariate time series anomalies often manifest as shifts in cross-channel dependencies rather than simple amplitude excursions. In autonomo

agentsarxiv-cs-ai

Symbolic Intermediaries as a Linguistic-Numerical Interface for LLM-Driven Geometric Reasoning

arXiv:2505.17607v3 Announce Type: replace Abstract: Large Language Models (LLMs) display reasoning capabilities over linguistic and symbolic objects but have limited capabilities to directly interpret

Targeted Speaker Poisoning Framework in Zero-Shot Text-to-Speech

arXiv:2603.07551v2 Announce Type: replace-cross Abstract: Zero-shot Text-to-Speech (TTS) voice cloning poses severe privacy risks, demanding the removal of specific speaker identities from trained TTS

The Regularizing Power of Language-Training Deepfake Detectors

model-releasesarxiv-cs-cv

arXiv:2605.31192v1 Announce Type: new Abstract: Recently, thanks to the advent of Multimodal-LLMs, deepfake detectors are striving not only to be generalizable but also interpretable. We propose that

UniAudio-Token: Empowering Semantic Speech Tokenizers with General Audio Perception

arXiv:2605.31521v1 Announce Type: new Abstract: Semantic speech tokenizers have become a widely used interface for Audio-LLMs, owing to their compact single-codebook design and strong linguistic align

safetyarxiv-cs-cl

Variational Adapter for Cross-modal Similarity Representation

arXiv:2605.30968v1 Announce Type: cross Abstract: The core of vision-language models lies in measuring cross-modal similarity within a unified representation space. However, most image-text matching o

View Space: Learning Representation across Arbitrary Graphs

arXiv:2512.11561v2 Announce Type: replace Abstract: Generalizing pretrained models to unseen datasets without retraining is a central challenge toward foundation models. Achieving fully inductive infe

What Am I Missing? Question-Answering as Hidden State Probing

arXiv:2605.31561v1 Announce Type: new Abstract: Test-time reasoning has become a significant field of study since the introduction of chain-of-thought reasoning in large language models (LLMs). Howeve

safetyarxiv-cs-cl

What Gets Unmasked First? Trajectory Analysis of Diffusion Models for Graph-to-Text Generation

arXiv:2605.31564v1 Announce Type: cross Abstract: We present the first systematic study of masked diffusion language models (MDLMs) for graph-to-text generation. We analyze MDLM generation trajectorie

WristCompass: Kinematic Coupling as a Learnable Visual Concept for Ego-Camera Orientation

model-releasesarxiv-cs-cv

arXiv:2605.30671v1 Announce Type: new Abstract: Recovering ego-camera orientation from manipulation video is a prerequisite for disentangling hand motion from camera motion, a key step in imitation le

ZAPS-DA: Zero-Phase Action Policy Smoothing with Decoupled Actor for Continuous Control in Reinforcement Learning

arXiv:2605.30612v1 Announce Type: cross Abstract: Continuous control policies trained with off-policy reinforcement learning frequently exhibit high-frequency action jitter, rendering direct deploymen