Search: “models”

The Collaboration Gap in Human-AI Work

arXiv:2604.18096v1 Announce Type: cross Abstract: LLMs are increasingly presented as collaborators in programming, design, writing, and analysis. Yet the practical experience of working with them ofte

Agents

The Thin Line Between Comprehension and Persuasion in LLMs

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arXiv:2507.01936v3 Announce Type: replace Abstract: Large language models (LLMs) are excellent at maintaining high-level, convincing dialogue, but it remains unclear whether their persuasive success r

agentsarxiv-cs-cl

21 Apr 2026

The Virtue of Sparsity in Complexity

model-releasesarxiv-cs-lg

arXiv:2604.17166v1 Announce Type: cross Abstract: Sparsity or complexity? In modern high-dimensional asset pricing, these are often viewed as competing principles: richer feature spaces appear to favo

Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks

arXiv:2604.16834v1 Announce Type: cross Abstract: Privacy-preserving machine learning (PPML) has become increasingly important in applications where sensitive data must remain confidential. Homomorphi

Towards Robust Text-to-Image Person Retrieval: Multi-View Reformulation for Semantic Compensation

arXiv:2604.18376v1 Announce Type: new Abstract: In text-to-image person retrieval tasks, the diversity of natural language expressions and the implicitness of visual semantics often lead to the proble

Towards Universal Skeleton-Based Action Recognition

arXiv:2604.17013v1 Announce Type: new Abstract: With the development of robotics, skeleton-based action recognition has become increasingly important, as human-robot interaction requires understanding

Tri-Modal Fusion Transformers for UAV-based Object Detection

arXiv:2604.16630v1 Announce Type: new Abstract: Reliable UAV object detection requires robustness to illumination changes, motion blur, and scene dynamics that suppress RGB cues. Thermal long-wave inf

Local Ai

Trustworthy Endoscopic Super-Resolution

arXiv:2604.18001v1 Announce Type: new Abstract: Super-resolution (SR) models are attracting growing interest for enhancing minimally invasive surgery and diagnostic videos under hardware constraints.

local-aiarxiv-cs-cv

UGD: An Unsupervised Geometric Distance for Evaluating Real-world Noisy Point Cloud Denoising

arXiv:2604.16976v1 Announce Type: new Abstract: Point cloud denoising is a fundamental and crucial challenge in real-world point cloud applications. Existing quantitative evaluation metrics for point

tutorialsarxiv-cs-cv

UniCSG: Unified High-Fidelity Content-Constrained Style-Driven Generation via Staged Semantic and Frequency Disentanglement

arXiv:2604.17850v1 Announce Type: new Abstract: Style transfer must match a target style while preserving content semantics. DiT-based diffusion models often suffer from content-style entanglement, le

VIDS: A Verified Imaging Dataset Standard for Medical AI

arXiv:2604.17525v1 Announce Type: cross Abstract: Medical imaging AI development is fundamentally dependent on annotated datasets, yet no existing standard provides machine-enforceable validation acro

Applications

Vision-Braille: A Curriculum Learning Toolkit and Braille-Chinese Corpus for Braille Translation

arXiv:2407.06048v2 Announce Type: replace Abstract: We present Vision-Braille, the first publicly available end-to-end system for translating Chinese Braille extracted from images into written Chinese

applicationsarxiv-cs-cl

Weakly-Supervised Referring Video Object Segmentation through Text Supervision

arXiv:2604.17797v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) aims to segment the target instance in a video, referred by a text expression. Conventional approaches are mo

When Spike Sparsity Does Not Translate to Deployed Cost: VS-WNO on Jetson Orin Nano

model-releasesarxiv-cs-lg

arXiv:2604.17040v1 Announce Type: new Abstract: Spiking neural operators are appealing for neuromorphic edge computing because event-driven substrates can, in principle, translate sparse activity into

Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention

arXiv:2510.04212v3 Announce Type: replace Abstract: The pursuit of computational efficiency has driven the adoption of low-precision formats for training transformer models. However, this progress is

safetyarxiv-cs-lg

Why Training-Free Token Reduction Collapses: The Inherent Instability of Pairwise Scoring Signals

arXiv:2604.16745v1 Announce Type: cross Abstract: Training-free token reduction methods for Vision Transformers (ToMe, ToFu, PiToMe, and MCTF) employ different scoring mechanisms, yet they share a clo

researcharxiv-cs-cv

WorldDB: A Vector Graph-of-Worlds Memory Engine with Ontology-Aware Write-Time Reconciliation

model-releasesarxiv-cs-cl

arXiv:2604.18478v1 Announce Type: cross Abstract: Persistent memory is the bottleneck separating stateless chatbots from long-running agentic systems. Retrieval-augmented generation (RAG) over flat ve

A methodology to rank importance of frequencies and channels in electromyography data with Decision Tree classifiers

arXiv:2604.15353v1 Announce Type: cross Abstract: This study presents a methodology for identifying the most informative frequencies and channels in electromyography (EMG) data to evaluate muscle reco

tutorialsarxiv-cs-lg

ASMR-Bench: Auditing for Sabotage in ML Research

arXiv:2604.16286v1 Announce Type: new Abstract: As AI systems are increasingly used to conduct research autonomously, misaligned systems could introduce subtle flaws that produce misleading results wh

Agents

AstroVLM: Expert Multi-agent Collaborative Reasoning for Astronomical Imaging Quality Diagnosis

arXiv:2604.16024v1 Announce Type: cross Abstract: Vision Language Models (VLMs) have been applied to several specific domains and have shown strong problem-solving capabilities. However, astronomical

agentsarxiv-cs-cv

ATTNPO: Attention-Guided Process Supervision for Efficient Reasoning

arXiv:2602.09953v2 Announce Type: replace Abstract: Large reasoning models trained with reinforcement learning and verifiable rewards (RLVR) achieve strong performance on complex reasoning tasks, yet

researcharxiv-cs-cl

AutoFed: Personalized Federated Traffic Prediction via Adaptive Prompt

arXiv:2512.24625v2 Announce Type: replace-cross Abstract: Accurate traffic prediction is essential for Intelligent Transportation Systems, including ride-hailing, urban road planning, and vehicle flee

Applications

AutoNFS: Automatic Neural Feature Selection

arXiv:2503.13304v2 Announce Type: replace Abstract: Feature selection (FS) is a fundamental challenge in machine learning, particularly for high-dimensional tabular data, where interpretability and co

applicationsarxiv-cs-lg

CLewR: Curriculum Learning with Restarts for Machine Translation Preference Learning

arXiv:2601.05858v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated competitive performance in zero-shot multilingual machine translation (MT). Some follow-up work

researcharxiv-cs-ai

COEVO: Co-Evolutionary Framework for Joint Functional Correctness and PPA Optimization in LLM-Based RTL Generation

arXiv:2604.15001v2 Announce Type: replace Abstract: LLM-based RTL code generation methods increasingly target both functional correctness and PPA quality, yet existing approaches universally decouple

Cross-modal learning for plankton recognition

arXiv:2603.16427v2 Announce Type: replace Abstract: This paper considers self-supervised cross-modal coordination as a strategy enabling utilization of multiple modalities and large volumes of unlabel

tutorialsarxiv-cs-cv

CTSCAN: Evaluation Leakage in Chest CT Segmentation and a Reproducible Patient-Disjoint Benchmark

arXiv:2604.15561v1 Announce Type: cross Abstract: Reported chest CT segmentation performance can be strongly inflated when train and test partitions mix slices from the same study. We present CTSCAN,

Deliberative Searcher: Improving LLM Reliability via Reinforcement Learning with constraints

arXiv:2507.16727v3 Announce Type: replace Abstract: Improving the reliability of large language models (LLMs) is critical for deploying them in real-world scenarios. In this paper, we propose extbf{De

safetyarxiv-cs-ai

Do LLMs Really Know What They Don't Know? Internal States Mainly Reflect Knowledge Recall Rather Than Truthfulness

arXiv:2510.09033v3 Announce Type: replace Abstract: Recent work suggests that LLMs 'know what they don't know', positing that hallucinated and factually correct outputs arise from distinct internal pr

researcharxiv-cs-cl

Driving Assistance System for Ambulances to Minimise the Vibrations in Patient Cabin

arXiv:2604.16047v1 Announce Type: cross Abstract: The ambulance service is the main transport for diseased or injured people which suffers the same acceleration forces as regular vehicles. These accel

Local Ai

Enhancing Visual Representation with Textual Semantics: Textual Semantics-Powered Prototypes for Heterogeneous Federated Learning

arXiv:2503.13543v2 Announce Type: replace-cross Abstract: Federated Prototype Learning (FedPL) has emerged as an effective strategy for handling data heterogeneity in Federated Learning (FL). In FedPL

local-aiarxiv-cs-ai

Evaluating quality in synthetic data generation for large tabular health datasets

arXiv:2604.15961v1 Announce Type: new Abstract: There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historic

EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs

arXiv:2604.15787v1 Announce Type: cross Abstract: We introduce EVIL (extbf{EV}olving extbf{I}nterpretable algorithms with extbf{L}LMs), an approach that uses LLM-guided evolutionary search to discover

researcharxiv-cs-ai

Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval Augmented Generation

arXiv:2505.21072v4 Announce Type: replace Abstract: Large Language Models (LLMs) enhanced with retrieval, an approach known as Retrieval-Augmented Generation (RAG), have achieved strong performance in

researcharxiv-cs-cl

From Zero to Detail: A Progressive Spectral Decoupling Paradigm for UHD Image Restoration with New Benchmark

arXiv:2604.15654v1 Announce Type: new Abstract: Ultra-high-definition (UHD) image restoration poses unique challenges due to the high spatial resolution, diverse content, and fine-grained structures p

IA-CLAHE: Image-Adaptive Clip Limit Estimation for CLAHE

arXiv:2604.16010v1 Announce Type: new Abstract: This paper proposes image-adaptive contrast limited adaptive histogram equalization (IA-CLAHE). Conventional CLAHE is widely used to boost the performan

Learning to Look before Learning to Like: Incorporating Human Visual Cognition into Aesthetic Quality Assessment

arXiv:2604.15853v1 Announce Type: new Abstract: Automated Aesthetic Quality Assessment (AQA) treats images primarily as static pixel vectors, aligning predictions with human-rating scores largely thro

Local Ai

MambaBack: Bridging Local Features and Global Contexts in Whole Slide Image Analysis

arXiv:2604.15729v1 Announce Type: cross Abstract: Whole Slide Image (WSI) analysis is pivotal in computational pathology, enabling cancer diagnosis by integrating morphological and architectural cues

local-aiarxiv-cs-ai

Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortion Detection

arXiv:2509.17292v3 Announce Type: replace-cross Abstract: Cognitive distortions have been closely linked to mental health disorders, yet their automatic detection remains challenging due to contextual

researcharxiv-cs-ai

MUSCAT: MUltilingual, SCientific ConversATion Benchmark

model-releasesarxiv-cs-cl

arXiv:2604.15929v1 Announce Type: new Abstract: The goal of multilingual speech technology is to facilitate seamless communication between individuals speaking different languages, creating the experi

NEFFY 2.0: A Breathing Companion Robot: User-Centered Design and Findings from a Study with Ukrainian Refugees

model-releasesarxiv-cs-ro

arXiv:2604.15325v1 Announce Type: cross Abstract: This paper presents the design of NEFFY 2.0, a social robot designed as a haptic slow-paced breathing companion for stress reduction, and reports find

Neuromorphic Parameter Estimation for Power Converter Health Monitoring Using Spiking Neural Networks

model-releasesarxiv-cs-lg

arXiv:2604.15714v1 Announce Type: cross Abstract: Always-on converter health monitoring demands sub-mW edge inference, a regime inaccessible to GPU-based physics-informed neural networks. This work se

On Optimal Hyperparameters for Differentially Private Deep Transfer Learning

arXiv:2510.20616v2 Announce Type: replace Abstract: Differentially private (DP) transfer learning, i.e., fine-tuning a pretrained model on private data, is the current state-of-the-art approach for tr

tutorialsarxiv-cs-lg

Photonic AI: A Hybrid Diffractive Holographic Neural System for Passive Optical Real-Time Image Classification

arXiv:2604.15364v1 Announce Type: cross Abstract: Edge intelligence is constrained by the energy and latency costs of shuttling data through electronic memory hierarchies. Optical systems offer a fund

PolicyBank: Evolving Policy Understanding for LLM Agents

arXiv:2604.15505v1 Announce Type: cross Abstract: LLM agents operating under organizational policies must comply with authorization constraints typically specified in natural language. In practice, su

Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All

arXiv:2411.09355v3 Announce Type: replace-cross Abstract: We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially

Ranking XAI Methods for Head and Neck Cancer Outcome Prediction

arXiv:2604.16034v1 Announce Type: new Abstract: For head and neck cancer (HNC) patients, prognostic outcome prediction can support personalized treatment strategy selection. Improving prediction perfo

researcharxiv-cs-cv

Revisiting Entropy Regularization: Adaptive Coefficient Unlocks Its Potential for LLM Reinforcement Learning

arXiv:2510.10959v3 Announce Type: replace-cross Abstract: Reasoning ability has become a defining capability of Large Language Models (LLMs), with Reinforcement Learning with Verifiable Rewards (RLVR)

safetyarxiv-cs-ai