Search: “multimodal”

Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents

arXiv:2604.18122v1 Announce Type: new Abstract: Decision-making is a cognitively intensive task that requires synthesizing relevant information from multiple unstructured sources, weighing competing f

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Deep Hierarchical Knowledge Loss for Fault Intensity Diagnosis

DGX agent

arXiv:2604.16459v1 Announce Type: cross Abstract: Fault intensity diagnosis (FID) plays a pivotal role in intelligent manufacturing while neglecting dependencies among target classes hinders its pract

applicationsarxiv-cs-cv

21 Apr 2026

DiffuSAM: Diffusion Guided Zero-Shot Object Grounding for Remote Sensing Imagery

arXiv:2604.18201v1 Announce Type: new Abstract: Diffusion models have emerged as powerful tools for a wide range of vision tasks, including text-guided image generation and editing. In this work, we e

Do LLMs Use Cultural Knowledge Without Being Told? A Multilingual Evaluation of Implicit Pragmatic Adaptation

arXiv:2604.17718v1 Announce Type: new Abstract: Many benchmarks show that large language models can answer direct questions about culture. We study a different question: do they also change how they s

Document-as-Image Representations Fall Short for Scientific Retrieval

model-releasesarxiv-cs-cl

arXiv:2604.18508v1 Announce Type: cross Abstract: Many recent document embedding models are trained on document-as-image representations, embedding rendered pages as images rather than the underlying

DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies

arXiv:2503.14324v3 Announce Type: replace-cross Abstract: The differing representation spaces required for visual understanding and generation pose a challenge in unifying them within the autoregressi

EmbodiedHead: Real-Time Listening and Speaking Avatar for Conversational Agents

arXiv:2604.17211v1 Announce Type: new Abstract: We present EmbodiedHead, a speech-driven talking-head framework that equips LLMs with real-time visual avatars for conversation. A practical embodied av

Empowering Multi-Turn Tool-Integrated Agentic Reasoning with Group Turn Policy Optimization

arXiv:2511.14846v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) for multi-turn Tool-Integrated Reasoning (TIR) - where models iteratively reason, generate code, and ver

FireScope: Wildfire Risk Prediction with a Chain-of-Thought Oracle

arXiv:2511.17171v4 Announce Type: replace Abstract: Predicting wildfire risk is a reasoning-intensive spatial problem that requires the integration of visual, climatic, and geographic factors to infer

FrameVGGT: Geometry-Aligned Frame-Level Memory for Bounded Streaming VGGT

arXiv:2603.07690v2 Announce Type: replace Abstract: Streaming Visual Geometry Transformers such as StreamVGGT enable strong online 3D perception, but their KV-cache grows unbounded over long streams,

Frozen Vision Transformers for Dense Prediction on Small Datasets: A Case Study in Arrow Localization

arXiv:2604.16758v1 Announce Type: new Abstract: We present a system for automated detection, localization, and scoring of arrow punctures on 40,cm indoor archery target faces, trained on only 48 annot

applicationsarxiv-cs-cv

Geometric Stability: The Missing Axis of Representations

arXiv:2601.09173v4 Announce Type: replace-cross Abstract: Representational similarity analysis and related methods have become standard tools for comparing the internal geometries of neural networks a

High-Resolution Visual Reasoning via Multi-Turn Grounding-Based Reinforcement Learning

arXiv:2507.05920v2 Announce Type: replace Abstract: State-of-the-art large multi-modal models (LMMs) face challenges when processing high-resolution images, as these inputs are converted into enormous

HiPrune: Hierarchical Attention for Efficient Token Pruning in Vision-Language Models

arXiv:2508.00553v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) encode images and videos into abundant tokens, which contain substantial redundancy and computation cost. While visual

Hybrid Multi-Dimensional MRI Prostate Cancer Detection via Hadamard Network-Based Bias Correction and Residual Networks

arXiv:2604.17107v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) is vital for prostate cancer (PCa) diagnosis. While advanced techniques such as Hybrid Multi-dimensional MRI (HM-MRI) h

Hybrid Quantum Neural Networks for Enhanced Breast Cancer Thermographic Classification: A Novel Quantum-Classical Integration Approach

arXiv:2604.16953v1 Announce Type: cross Abstract: Breast cancer diagnosis through thermographic image analysis remains a critical challenge in medical AI, with classical deep learning approaches facin

applicationsarxiv-cs-cv

Hyperbolic Enhanced Representation Learning for Incomplete Multi-view Clustering

arXiv:2604.16959v1 Announce Type: cross Abstract: Incomplete Multi-View Clustering (IMVC) faces the challenge of learning discriminative representations from fragmentary observations while maintaining

Improving Speech Recognition of Named Entities in Classroom Speech with LLM Revision and Phonetic-Semantic Context

arXiv:2506.10779v2 Announce Type: replace Abstract: Classroom speech and lectures often contain named entities (NEs) such as names of people and special terminology. While automatic speech recognition

LLaMA-XR: A Novel Framework for Radiology Report Generation using LLaMA and QLoRA Fine Tuning

arXiv:2506.03178v2 Announce Type: replace-cross Abstract: Automated radiology report generation holds significant potential to reduce radiologists' workload and enhance diagnostic accuracy. However, g

LLM as Graph Kernel: Rethinking Message Passing on Text-Rich Graphs

arXiv:2603.14937v2 Announce Type: replace-cross Abstract: Text-rich graphs, which integrate complex structural dependencies with abundant textual information, are ubiquitous yet remain challenging for

LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains

arXiv:2604.16379v1 Announce Type: cross Abstract: Industrial B2B applications (e.g., construction site risk prediction, material procurement) face extreme data sparsity yet feature rich textual intera

Agents

MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation

arXiv:2604.18509v1 Announce Type: new Abstract: Large language models (LLMs) are widely used in retrieval-augmented generation (RAG) to incorporate external knowledge at inference time. However, when

agentsarxiv-cs-cl

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

arXiv:2604.18418v1 Announce Type: new Abstract: Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medici

Tutorials

MM-Hand: A 21-DOF Multi-modal Modular Dexterous Robotic Hand with Remote Actuation

arXiv:2604.17245v1 Announce Type: new Abstract: High-DOF dexterous hands require compact actuation, rich sensing, and reliable thermal behavior, but conventional designs often occupy valuable in-hand

tutorialsarxiv-cs-ro

MoVE: Translating Laughter and Tears via Mixture of Vocalization Experts in Speech-to-Speech Translation

arXiv:2604.17435v1 Announce Type: new Abstract: Recent Speech-to-Speech Translation (S2ST) systems achieve strong semantic accuracy yet consistently strip away non-verbal vocalizations (NVs), such as

applicationsarxiv-cs-cl

Multilingual Training and Evaluation Resources for Vision-Language Models

arXiv:2604.18347v1 Announce Type: new Abstract: Vision Language Models (VLMs) achieved rapid progress in the recent years. However, despite their growth, VLMs development is heavily grounded on Englis

NaviFormer: A Deep Reinforcement Learning Transformer-like Model to Holistically Solve the Navigation Problem

arXiv:2604.16967v1 Announce Type: new Abstract: Path planning is usually solved by addressing either the (high-level) route planning problem (waypoint sequencing to achieve the final goal) or the (low

applicationsarxiv-cs-ro

Navigating Distribution Shifts in Medical Image Analysis: A Survey

arXiv:2411.05824v3 Announce Type: replace-cross Abstract: Medical Image Analysis (MedIA) has become indispensable in modern healthcare, enhancing clinical diagnostics and personalized treatment. Despi

Negative Advantage Is a Double-Edged Sword: Calibrating Advantage in GRPO for Deep Search

arXiv:2604.18235v1 Announce Type: new Abstract: Deep search agents can autonomously initiate multi-turn interactions with search engines, thereby exhibiting strong question-answering capabilities. Suc

OmniHuman: A Large-scale Dataset and Benchmark for Human-Centric Video Generation

arXiv:2604.18326v1 Announce Type: new Abstract: Recent advancements in audio-video joint generation models have demonstrated impressive capabilities in content creation. However, generating high-fidel

On the Robustness of LLM-Based Dense Retrievers: A Systematic Analysis of Generalizability and Stability

arXiv:2604.16576v1 Announce Type: cross Abstract: Decoder-only large language models (LLMs) are increasingly replacing BERT-style architectures as the backbone for dense retrieval, achieving substanti

One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection

arXiv:2604.18393v1 Announce Type: new Abstract: Diffusion models have achieved outstanding performance in unsupervised industrial anomaly detection (uIAD) by learning a manifold of normal data under t

Predicting Blastocyst Formation in IVF: Integrating DINOv2 and Attention-Based LSTM on Time-Lapse Embryo Images

arXiv:2604.16505v1 Announce Type: new Abstract: The selection of the optimal embryo for transfer is a critical yet challenging step in in vitro fertilization (IVF), primarily due to its reliance on th

Preparation of Fractal-Inspired Computational Architectures for Automated Neural Design Exploration

arXiv:2511.07329v3 Announce Type: replace-cross Abstract: It introduces FractalNet, a fractal-inspired computational architectures for advanced large language model analysis that mainly challenges mod

Progressive Online Video Understanding with Evidence-Aligned Timing and Transparent Decisions

arXiv:2604.18459v1 Announce Type: new Abstract: Visual agents operating in the wild must respond to queries precisely when sufficient evidence first appears in a video stream, a critical capability th

ProtoCLIP: Prototype-Aligned Latent Refinement for Robust Zero-Shot Chest X-Ray Classification

arXiv:2604.18444v1 Announce Type: cross Abstract: Zero-shot vision-language models (VLMs) have shown promise for chest radiograph classification, but their performance is often limited by confounding

ReCoQA: A Benchmark for Tool-Augmented and Multi-Step Reasoning in Real Estate Question and Answering

model-releasesarxiv-cs-cl

arXiv:2604.17944v1 Announce Type: new Abstract: Developing agents capable of navigating fragmented, multi-source information remains challenging, primarily due to the scarcity of benchmarks reflecting

Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging

arXiv:2604.17222v1 Announce Type: new Abstract: Breast cancer diagnosis demands rapid and precise tools, yet traditional histopathological methods often fall short in intra-operative settings. Deep Ul

Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning

arXiv:2601.14750v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting has achieved remarkable success in unlocking the reasoning capabilities of Large Language Models (LLMs). Although C

Local Ai

Revisiting Entropy in Reinforcement Learning for Large Reasoning Models

arXiv:2511.05993v3 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for enhancing the reasoning capabilities of large language

local-aiarxiv-cs-cl

Robust Diabetic Retinopathy Grading Using Dual-Resolution Attention-Based Deep Learning with Ordinal Regression

arXiv:2604.17341v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, and automated grading systems play a crucial role in large-scale screening

Speculative Verification: Exploiting Information Gain to Refine Speculative Decoding

arXiv:2509.24328v2 Announce Type: replace Abstract: LLMs have low GPU efficiency and high latency due to autoregressive decoding. Speculative decoding (SD) mitigates this using a small draft model to

SpiralThinker: Latent Reasoning through an Iterative Process with Text-Latent Interleaving

arXiv:2511.08983v2 Announce Type: replace Abstract: Recent advances in large reasoning models have been driven by reinforcement learning and test-time scaling, accompanied by growing interest in laten

StageMem: Lifecycle-Managed Memory for Language Models

arXiv:2604.16774v1 Announce Type: new Abstract: Long-horizon language model systems increasingly rely on persistent memory, yet many current designs still treat memory primarily as a static store: wri

TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications

model-releasesarxiv-cs-lg

arXiv:2604.17778v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in the telecommunications domain for critical tasks, relying heavily on Retrieval-Augmented Gener

The Role of Vocabularies in Learning Sparse Representations for Ranking

arXiv:2509.16621v2 Announce Type: replace-cross Abstract: Learned Sparse Retrieval (LSR) such as SPLADE has growing interest for effective semantic 1st stage matching while enjoying the efficiency of

applicationsarxiv-cs-cl

Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data

model-releasesarxiv-cs-lg

arXiv:2604.18493v1 Announce Type: new Abstract: Reinforcement Learning (RL) enhances LLM reasoning, yet a paradox emerges as models scale: strong base models saturate standard benchmarks (e.g., MATH),

Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement

arXiv:2604.06155v2 Announce Type: replace-cross Abstract: Whether Large Language Models (LLMs) develop coherent internal world models remains a core debate. While conventional Next-Token Prediction (N