Search: “inference”

arXiv:2607.23193v1 Announce Type: new Abstract: Existing token compression methods for omnimodal large language models typically rely on one modality to determine what to retain in the other. We show

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Model Releases

Out-of-Length Scene Text Recognition: A Two-Axis Diagnosis and a Training-Free Fix

DGX agent

arXiv:2607.23194v1 Announce Type: new Abstract: Scene Text Recognition (STR) models are trained almost exclusively on word crops of at most 25 characters, yet real deployments (signage, product labels

model-releasesarxiv-cs-cv

28 Jul 2026

ParasGB: A Graph Benchmark Suite for Parasitic Estimation on AMS Circuits

model-releasesarxiv-cs-lg

arXiv:2607.23225v1 Announce Type: new Abstract: As chip manufacturing processes advance to deep submicron nodes, parasitic interconnect effects increasingly dominate the performance of analog and mixe

Tutorials

PathSelect: Sequential Token Selection for Whole Slide Pathology

arXiv:2607.23631v1 Announce Type: new Abstract: Gigapixel Whole-Slide Images (WSIs) present a fundamental computational bottleneck for vision-language models (VLMs) due to extreme sequence lengths. Ex

tutorialsarxiv-cs-cv

Phenology-based learning framework for yield estimation and harvest forecasting of raspberry fruits

model-releasesarxiv-cs-cv

arXiv:2411.00967v2 Announce Type: replace Abstract: The future of agriculture is intertwined with automation. Accurate fruit detection, yield estimation, and harvest time prediction are crucial for ef

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention

model-releasesarxiv-cs-cl

arXiv:2607.24593v1 Announce Type: new Abstract: Token-level sparse attention, as implemented by DeepSeek Sparse Attention (DSA) in production systems, makes the downstream attention efficient but shif

Hardware

Real-Time Semantic Segmentation with Optimized RetinaNet Architectures for Embedded Automotive Systems

arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat

hardwarearxiv-cs-ai

Reason Popper-ly: Patching In-Context Reasoning with Inductive Logic Programming

arXiv:2607.23019v1 Announce Type: new Abstract: Chain-of-thought (CoT) prompting enables large language models (LLMs) to tackle multi-step reasoning tasks, yet the generated intermediate steps are not

ReflexTrack: A Feedback-Driven Agent for Training-Free Referring Video Object Segmentation

arXiv:2607.24098v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) requires segmenting a target specified by natural language throughout a video. Recent agentic approaches comb

local-aiarxiv-cs-cv

Restoration Flow Matching-Based Channel Refinement and Equalization Correction for MIMO Semantic Communications

arXiv:2607.23615v1 Announce Type: new Abstract: In multiple-input multiple-output (MIMO) semantic communication, imperfect channel state information (CSI) and equalization mismatch can seriously degra

Rethinking Classifier-Free Guidance in On-Policy Diffusion Distillation

arXiv:2607.24731v1 Announce Type: cross Abstract: On-policy distillation (OPD) adapts diffusion models by querying a teacher along trajectories generated by the current student, but how it should beha

safetyarxiv-cs-ai

RP-OPSD: Resolution-Privileged On-Policy Self-Distillation for Multimodal Large Language Models

arXiv:2607.24447v1 Announce Type: new Abstract: On-Policy Self-Distillation (OPSD) uses privileged information available only to the teacher to provide dense token-level supervision on trajectories ge

local-aiarxiv-cs-cv

SADe: Sparse-Atom Support Decontamination for Few-Shot Segmentation with Weak Support Annotations

arXiv:2607.24706v1 Announce Type: new Abstract: Few-shot segmentation (FSS) commonly assumes clean pixel-level support masks, yet practical support supervision often uses boxes, scribbles, coarse mask

researcharxiv-cs-cv

SafeCRS: Personalized Safety Alignment for LLM-Based Conversational Recommender Systems

arXiv:2603.03536v2 Announce Type: replace-cross Abstract: Current LLM-based conversational recommender systems (CRS) primarily optimize recommendation accuracy and user satisfaction. We identify an un

Same Question, Different Answers: Evaluating LLM Reliability Beyond Accuracy

arXiv:2607.22554v1 Announce Type: new Abstract: Large language models (LLMs) often achieve strong accuracy on benchmarks, yet it remains unclear how reliably they apply this knowledge when the same qu

researcharxiv-cs-ai

Scale Weight Decay and Train Better

arXiv:2607.23777v1 Announce Type: cross Abstract: The discovery of scaling laws has motivated training neural networks on ever increasing quantities of data. This is typically done with a constant dec

Agents

Scaling GUI Agents with Visual State Transitions

arXiv:2607.24112v1 Announce Type: new Abstract: We introduce State Transition Pretraining (STP) as a new scaling axis for GUI agents. During the STP stage, we continually pretrain a unified multimodal

agentsarxiv-cs-ai

scMIR: a vision-language foundation model for single-cell light microscopy image representation

arXiv:2607.22712v1 Announce Type: cross Abstract: Single-cell light microscopy images have become an important data source for characterizing cell phenotypes, but their complexity and heterogeneity po

Semalith v1.4: A Calibrated 184M Safety Classifier Achieving State-of-the-Art Prompt-Injection Detection at 44x Fewer Parameters than Llama-Guard-3-8B

arXiv:2607.22545v1 Announce Type: cross Abstract: Deploying large language models in financial-services and agentic settings requires safety classifiers that simultaneously handle prompt injection, re

Applications

SeT-Diff: Towards Semantic Foundation Models for HPC Telemetry and Time-Series

arXiv:2607.22548v1 Announce Type: new Abstract: Data centers and their compute nodes require accurate and flexible digital twins capable of modeling the complex interplay of workloads, environmental p

applicationsarxiv-cs-ai

Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI

arXiv:2607.22953v1 Announce Type: new Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a m

local-aiarxiv-cs-ai

Similarity All The Way Up: Multilingual Generalization in LLMs Relies on Language-Level Similarity Structures

arXiv:2607.22699v1 Announce Type: new Abstract: As Large Language Models (LLMs) grow more capable across diverse tasks, their (in)ability to generalize remains difficult to quantify and poorly underst

SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads

arXiv:2607.23121v1 Announce Type: cross Abstract: Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-s

researcharxiv-cs-cl

Hardware

Spatial-IQ: Deconstructing Spatial Intelligence via Hierarchical Capability Tests

arXiv:2607.22864v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) excel at visual interpretation but fail on spatial reasoning tasks that humans solve reliably. Existing bench

hardwarearxiv-cs-ai

Agents

SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving

arXiv:2607.23933v1 Announce Type: cross Abstract: As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces

agentsarxiv-cs-ai

StanceBench: A Benchmark for Audio LLM-Based Interpersonal Stance Evaluation from Speech

arXiv:2607.22658v1 Announce Type: new Abstract: Speech-to-speech dialogue models increasingly depend on prosody and interactional nuance to convey social intent, yet benchmarks for these cues remain l

StanceFlip: A Comprehensive Multi-Dimensional Benchmark for Multimodal Conversational Stance Flipping Forecasting

arXiv:2607.24191v1 Announce Type: cross Abstract: Conversational stance detection has shifted from static text analysis to dynamic multimodal modeling. However, existing benchmarks exhibit three key l

Steerable Chatbots: Exploring Personalization Control Interfaces via LLM Activation Steering

arXiv:2505.04260v3 Announce Type: replace-cross Abstract: Personalizing LLM responses typically requires users to articulate their preferences through prompting, which can be burdensome at cold start

researcharxiv-cs-ai

Structured Redundancy Modeling for Efficient Visual Token Pruning in High-Resolution MLLMs

arXiv:2607.23046v1 Announce Type: new Abstract: Recent high-resolution Multimodal Large Language Models (MLLMs) generate thousands of visual tokens per input, leading to a visual token explosion that

safetyarxiv-cs-cv

TaoMate: Anchor-Guided Memory Bridging Evolving and Reference States for Real-Time Audio-Video Digital Human Generation

arXiv:2607.24359v1 Announce Type: new Abstract: Real-time long-form digital-human generation relies on causal models to extend audio-visual content while preserving subject appearance and audio-video

local-aiarxiv-cs-cv

TriSP: Tri-Signal Structured Pruning for Large Language Models

arXiv:2607.22587v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance across diverse tasks but their deployment is constrained by the memory and compute cost of their

Trustworthy Medical Segmentation: Uncertainty-Aware U-Net Evaluation Under Clinical Image Degradation

model-releasesarxiv-cs-cv

arXiv:2607.22727v1 Announce Type: new Abstract: Medical image segmentation models often report high benchmark accuracy under ideal imaging conditions, yet their failures under clinical degradation can

Variational-Ising-Attention (VIA):TailoredAttentionMattersfor Science

arXiv:2607.23634v1 Announce Type: cross Abstract: Attention enables context modeling via query-key scoring with softmax normalization. Driven by industrial long-context demands, mainstream research ha

researcharxiv-cs-ai

Visual Token Compression Enhances Robustness of MLLMs

arXiv:2607.22716v1 Announce Type: new Abstract: In this paper, we show for the first time that visual token pruning enhances the robustness of Multimodal Large Language Models (MLLMs), mitigating vuln

safetyarxiv-cs-cv

VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs

model-releasesarxiv-cs-ro

arXiv:2512.22342v5 Announce Type: replace Abstract: In most existing embodied navigation tasks, instructions are well-defined and unambiguous, such as instruction following and object searching. Under

When LLM Defenses Backfire: Characterizing Safety, Performance, and Cost Trade-offs

model-releasesarxiv-cs-lg

arXiv:2607.24392v1 Announce Type: cross Abstract: Jailbreak defenses are essential for protecting large language models (LLMs), but they can also introduce secondary costs that weaken model utility. W

Who Gets Named: Citation Type Predicts Individual Naming by Grounded Language Models, and a Roster Instrument Captures 0.5% of It

model-releasesarxiv-cs-cl

arXiv:2607.23893v1 Announce Type: cross Abstract: Prior work on AI brand visibility measures the firm: does a model recommend a company, and does that track its reputation. This study asks the questio

A Factorial Study of Synthetic Data Generation for Low-Resource Machine Translation using Grammar Books

arXiv:2607.22376v1 Announce Type: new Abstract: Most endangered languages lack the parallel data required for machine translation, despite the existence of descriptive grammar books. We introduce a pi

researcharxiv-cs-cl

A Smooth Phase-Separation Model for Weak-Boundary Segmentation of Homogeneous Structures

arXiv:2607.22053v1 Announce Type: new Abstract: Segmentation of adjacent structures with similar intensity distributions remains a challenging problem in image analysis, particularly when object bound

researcharxiv-cs-cv

Adaptive Undulatory Locomotion of Snake-like Robots in Dynamic Viscous Environments via Deep Reinforcement Learning

arXiv:2607.21960v1 Announce Type: new Abstract: This paper demonstrates how deep reinforcement learning (DRL) enables adaptive locomotion of snake-like robots in dynamically changing viscous environme

safetyarxiv-cs-ro

AgentHOI: Multi-Agent Reasoning for Human-Object-Interaction Video Generation via Implicit Representation Alignment

arXiv:2607.22241v1 Announce Type: new Abstract: Recent advances in video diffusion models have spurred interest in human-object interaction (HOI) video generation, which demands fine-grained control o

safetyarxiv-cs-cv

Agents

Agentic Root Cause Analysis through Evidence-Grounded Reasoning

arXiv:2607.22385v1 Announce Type: cross Abstract: Diagnosing the root cause of anomalies is essential for safe industrial operation. Despite extensive sensor instrumentation, formulating hypotheses an

agentsarxiv-cs-lg

Ask for More Than Bayes Optimal: A Theory of Indecisions for Selective Hypothesis Testing

arXiv:2412.12807v4 Announce Type: replace-cross Abstract: Selective classification is a powerful tool for automated decision-making in high-risk scenarios, allowing classifiers to act only when confid

Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness

model-releasesarxiv-cs-lg

arXiv:2607.21806v1 Announce Type: new Abstract: Predictive machine learning (ML) models are increasingly used to aid human decision-makers across various high-risk domains such as healthcare and crimi

Cross-reality location privacy protection in 6G-enabled vehicular metaverses: an LLM-enhanced hybrid generative diffusion model-based approach

arXiv:2601.12311v2 Announce Type: replace-cross Abstract: The emergence of 6G-enabled vehicular metaverses enables Autonomous Vehicles (AVs) to operate across physical and virtual spaces through space

safetyarxiv-cs-lg

Deep Sigma Point Processes for RCS Modeling in Spaceborne SAR Imagery

arXiv:2607.21745v1 Announce Type: cross Abstract: Radar cross-section (RCS) modeling is foundational to advancing the utility and sensitivity of spaceborne radar systems. This study introduces a deep

Dysphagia Risk Stratification in Head and Neck Cancer via Two-Stage PRO-Clinical Stacking

arXiv:2607.22514v1 Announce Type: new Abstract: Dysphagia is a debilitating late effect of head and neck cancer (HNC) treatment, yet timely identification of at-risk patients remains challenging in su

Efficient Online LLM Watermark Detection via Rao-Blackwellized E-Processes

arXiv:2607.21958v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed, reliable and efficient mechanisms for distinguishing AI-generated text from human-written c