Search: “models”

Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness

arXiv:2605.02009v1 Announce Type: cross Abstract: Building on recent advances in representation learning for wireless channels, this work investigates the cost-benefit trade-offs of high-dimensional c

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Research

BoostDream: Efficient Refining for High-Quality Text-to-3D Generation from Multi-View Diffusion

DGX agent

arXiv:2401.16764v5 Announce Type: replace Abstract: Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary para

researcharxiv-cs-cv

5 May 2026

Hardware

Can AI Debias the News? LLM Interventions Improve Cross-Partisan Receptivity but LLMs Overestimate Their Own Effectiveness

arXiv:2605.01006v1 Announce Type: new Abstract: Partisan news media erode cross-partisan trust, but large language models (LLMs) offer a potential means of debiasing such content at scale. Across two

hardwarearxiv-cs-cl

Can LLMs Compress (and Decompress)? Evaluating Code Understanding and Execution via Invertibility

arXiv:2601.13398v2 Announce Type: replace Abstract: LLMs demonstrate strong performance on code benchmarks, yet consistent reasoning across forward and backward execution remains elusive. We present R

Channel-Level Relation to Attentive Aggregation with Neighborhood-Homogeneity Constraint for Point Cloud Analysis

arXiv:2605.02357v1 Announce Type: new Abstract: In 3D point cloud understanding, the core challenge lies in accurately capturing discriminative features within complex neighborhoods, which directly af

Applications

CLEAR: Revealing How Noise and Ambiguity Degrade Reliability in LLMs for Medicine

arXiv:2605.01011v1 Announce Type: new Abstract: Medical large language model (LLM) evaluations rely on simplified, exam-style benchmarks that rarely reflect the ambiguity of real-world medical inquiri

applicationsarxiv-cs-cl

COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following

arXiv:2509.04470v2 Announce Type: replace Abstract: Autonomous agents executing human instructions must operate reliably even when instructions are incomplete. While recent approaches improve detectio

Creating and Evaluating Figurative Language Dataset for Sindhi

arXiv:2605.01323v1 Announce Type: new Abstract: In this article, we introduce SiNFluD, a novel benchmark dataset for Sindhi figurative language classification. We first collect raw text from various b

CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing

arXiv:2602.15823v2 Announce Type: replace Abstract: A central challenge in large language model (LLM) editing is capability preservation: methods that successfully change targeted behavior can quietly

researcharxiv-cs-lg

Cross-Language Learning within Arabic Script for Low-Resource HTR

arXiv:2605.02089v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) under limited labeled data remains a challenging problem, particularly for Arabic-script languages. Although modern s

Democratizing the medieval English legal tradition

arXiv:2605.00977v1 Announce Type: cross Abstract: The record of the beginning of the most widespread legal system in the world is contained in millions of pages of handwritten text. Most of the record

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching

arXiv:2605.00941v1 Announce Type: cross Abstract: Flow matching has become a leading framework for generative modeling, but quantifying the uncertainty of its samples remains an open problem. Existing

DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning

arXiv:2605.02196v1 Announce Type: new Abstract: Machine unlearning aims to remove specified training data to satisfy privacy regulations such as GDPR. However, existing evaluations assume identical pr

DynamicPO: Dynamic Preference Optimization for Recommendation

arXiv:2605.00327v1 Announce Type: cross Abstract: In large language model (LLM)-based recommendation systems, direct preference optimization (DPO) effectively aligns recommendations with user preferen

researcharxiv-cs-ai

EdgeLPR: On the Deep Neural Network trade-off between Precision and Performance in LiDAR Place Recognition

arXiv:2605.02275v1 Announce Type: new Abstract: Place recognition is essential for long-term autonomous navigation, enabling loop closure and consistent mapping. Although deep learning has improved pe

Enhancing Game Review Sentiment Classification on Steam Platform with Attention-Based BiLSTM

arXiv:2605.01315v1 Announce Type: new Abstract: This paper investigates sentiment classification of Steam game reviews using an attention-based Bidirectional Long Short-Term Memory (BiLSTM) model. Usi

researcharxiv-cs-cl

Safety

Exploring Prompt Alignment with Clinical Factors in Zero-Shot Segmentation VLMs for NSCLC Tumor Segmentation

arXiv:2605.01266v1 Announce Type: new Abstract: Zero-shot vision-language models (VLMs) offer a promptable alternative to task-specific training for gross tumor volume (GTV) delineation in non-small-c

safetyarxiv-cs-cv

FeedbackLLM: Metadata driven Multi-Agentic Language Agnostic Test Case Generator with Evolving prompt and Coverage Feedback

arXiv:2605.01264v1 Announce Type: cross Abstract: Traditional approaches to test case generation often involve manual effort and incur significant computational overhead. Additionally, these approache

FlexSQL: Flexible Exploration and Execution Make Better Text-to-SQL Agents

arXiv:2605.02815v1 Announce Type: new Abstract: Text-to-SQL over large analytical databases requires navigating complex schemas, resolving ambiguous queries, and grounding decisions in actual data. Mo

Applications

Hall-Like Transversal Stress and Sandpile Criticality on Real Production Networks

arXiv:2605.01561v1 Announce Type: cross Abstract: This paper develops a Hall-Sandpile model of economic instability that combines a Hall-like transversal stress mechanism with sandpile threshold dynam

applicationsarxiv-cs-lg

HARMES: A Multi-Modal Dataset for Wearable Human Activity Recognition with Motion, Environmental Sensing and Sound

arXiv:2605.02596v1 Announce Type: new Abstract: With each sensing modality exhibiting inherent strengths and limitations, multi-modal approaches for wearable Human Activity Recognition (HAR) are becom

HiFi-Mamba: Dual-Stream W-Laplacian Enhanced Mamba for High-Fidelity MRI Reconstruction

arXiv:2508.09179v3 Announce Type: replace-cross Abstract: Reconstructing high-fidelity MR images from undersampled k-space data remains a challenging problem in MRI. While Mamba variants for vision ta

Instance-Aware Parameter Configuration in Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem

model-releasesarxiv-cs-ai

arXiv:2605.00572v1 Announce Type: new Abstract: Algorithm performance in combinatorial optimization is highly sensitive to parameter settings, while a single globally tuned configuration often fails t

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation

arXiv:2512.21788v3 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning of Diffusion Transformers (DiTs) for diverse, multi-conditional tasks often suffers from task interference when usin

Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues

arXiv:2605.01097v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led to the development of AI-powered tutoring systems that provide interactive support via dialogue

researcharxiv-cs-cl

Tutorials

Isotropic Fourier Neural Operators

arXiv:2605.02597v1 Announce Type: new Abstract: Fourier Neural Operators are deep learning models that learn mappings between function spaces and can be used to learn and solve partial differential eq

tutorialsarxiv-cs-lg

Logit-KL Flow Matching: Non-Autoregressive Text Generation via Sampling-Hybrid Inference

arXiv:2411.16821v5 Announce Type: replace Abstract: Non-autoregressive (NAR) language models offer notable efficiency in text generation by circumventing the sequential bottleneck of autoregressive de

researcharxiv-cs-cl

Agents

MedScribe: Clinically Grounded CT Reporting through Agentic Workflows

arXiv:2605.01779v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown potential for automated radiology report generation, yet existing approaches rely on global embedding compressi

agentsarxiv-cs-cv

Safety

Minimizing Collateral Damage in Activation Steering

arXiv:2605.01167v1 Announce Type: new Abstract: Activation steering is a method for controlling Large Language Model (LLM) behavior by intervening in its internal representations to increase the align

safetyarxiv-cs-lg

MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC

arXiv:2605.02509v1 Announce Type: new Abstract: Continual learning systems face a fundamental tension between plasticity -- acquiring new knowledge -- and stability -- retaining prior knowledge. We in

Multi-Perspective Transformers in ARC-AGI-2 Challenge

arXiv:2605.01154v1 Announce Type: new Abstract: ARC-AGI-2 is a benchmark of human-intuitive visual puzzles that measures a machine's ability to generalize from limited examples, interpret symbolic mea

OmniEncoder: See, Hear, and Feel Continuous Motion Like Humans With One Encoder

arXiv:2605.01506v1 Announce Type: new Abstract: Recent advances in omni-modal large language models have enabled remarkable progress in joint vision-audio understanding. However, prevailing architectu

Parameter Space Analysis through Guided Visual Interpolations

arXiv:2509.19202v2 Announce Type: replace-cross Abstract: We propose Parameter Space Analysis through Guided Visual Interpolations (ParamInter), a novel tool for high-dimensional input parameter space

Perturb and Correct: Post-Hoc Ensembles using Affine Redundancy

arXiv:2605.01632v1 Announce Type: new Abstract: Models that are indistinguishable on in-distribution data can behave very differently under distribution shift. We introduce Perturb-and-Correct (P&C),

researcharxiv-cs-lg

PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs

arXiv:2605.00929v1 Announce Type: new Abstract: Multivariate time series anomaly detection in ICS has attracted growing attention due to the increasing threat of cyber-physical attacks on critical inf

Applications

Pixel-to-4D: Camera-Controlled Image-to-Video Generation with Dynamic 3D Gaussians

arXiv:2601.00678v2 Announce Type: replace Abstract: Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an ess

applicationsarxiv-cs-cv

Pretraining on Sleep Data Improves non-Sleep Biosignal Tasks

arXiv:2605.02500v1 Announce Type: new Abstract: Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and

researcharxiv-cs-lg

Psychologically Potent, Computationally Invisible: LLMs Generate Social-Comparison Triggers They Fail to Detect

arXiv:2605.01017v1 Announce Type: new Abstract: We introduce Xiaohongshu Social Comparison Reader Elicitation (XHS-SCoRE), a reader-grounded benchmark for detecting if a text-only Xiaohongshu (RedNote

Quasi-Static Control of Discrete Cosserat Rod

arXiv:2605.01395v1 Announce Type: cross Abstract: In this paper, we design feedback control laws for soft robots modelled using the Cosserat rod, which is spatially discretised using the Piecewise Con

researcharxiv-cs-ro

RAFNet: Region-Aware Fusion Network for Pansharpening

arXiv:2605.02184v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) and high-resolution panchromati

Scaling Sequence-to-Sequence Generative Neural Rendering

arXiv:2510.04236v3 Announce Type: replace Abstract: We present Kaleido, a family of generative models designed for photorealistic, unified object- and scene-level neural rendering. Kaleido operates on

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking

arXiv:2605.00974v1 Announce Type: cross Abstract: LLMs are increasingly equipped with safety alignment mechanisms, yet recent studies demonstrate that they remain vulnerable to jailbreaking attacks th

Agents

To Call or Not to Call: A Framework to Assess and Optimize LLM Tool Calling

arXiv:2605.00737v1 Announce Type: new Abstract: Agentic AI architectures augment LLMs with external tools, unlocking strong capabilities. However, tool use is not always beneficial; some calls may be

agentsarxiv-cs-ai

Toward Culturally Grounded Natural Language Processing

arXiv:2603.26013v2 Announce Type: replace Abstract: Multilingual NLP is often treated as a route to global inclusion, but linguistic coverage and cultural competence frequently diverge. This paper syn

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents

model-releasesarxiv-cs-ai

arXiv:2510.05950v2 Announce Type: replace Abstract: Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and in

Tutorials

TrajRAG: Retrieving Geometric-Semantic Experience for Zero-Shot Object Navigation

arXiv:2605.01700v1 Announce Type: new Abstract: Existing zero-shot Object Goal Navigation (ObjectNav) methods often exploit commonsense knowledge from large language or vision-language models to guide

tutorialsarxiv-cs-cv

Local Ai

Trust, but Verify: Peeling Low-Bit Transformer Networks for Training Monitoring

arXiv:2605.02853v1 Announce Type: new Abstract: Understanding whether deep neural networks are effectively optimized remains challenging, as training occurs in highly nonconvex landscapes and standard

local-aiarxiv-cs-lg

Two-Pass Zero-Shot Temporal-Spatial Grounding of Rare Traffic Events in Surveillance Video

arXiv:2605.01512v1 Announce Type: new Abstract: Grounding traffic accidents in real CCTV footage is a rare-event problem where training on labeled accident video is often prohibited, yet accurate join