Search: “multimodal”

Where Does Robustness Live? Neuron-Guided Adaptation for Retrieval-Augmented Language Models

arXiv:2604.02194v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Language Models (RALMs) have shown strong potential in knowledge-intensive tasks, yet they remain vulnerable when retrieve

researcharxiv-cs-ai

1 Sept 2026

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Model Releases

Where Induction Runs Out: Description-Length Difficulty and the Memorisation Gap in Integer-Sequence Benchmarks

DGX agent

arXiv:2608.29411v1 Announce Type: new Abstract: Integer sequences from the On-Line Encyclopedia of Integer Sequences (OEIS) are increasingly used to benchmark mathematical reasoning in language models

model-releasesarxiv-cs-lg

1 Sept 2026

Whole-Body MRI Classification via Prompt-Based Clinical Conditioning

arXiv:2608.30824v1 Announce Type: new Abstract: Combining whole-body magnetic resonance imaging (WB-MRI) with clinical variables has the potential to improve systemic disease diagnosis by leveraging c

1 Sept 2026

You Know What I Mean: A Benchmark for Agentic Conversational Reference Grounding

arXiv:2608.29834v1 Announce Type: new Abstract: Collaborative conversations frequently contain references whose targets are indirect rather than named: resolving 'this looks like the fix discussed yes

1 Sept 2026

3D MRI-Based Alzheimer's Disease Classification Using Multi-Modal 3D CNN with Leakage-Aware Subject-Level Evaluation

model-releasesarxiv-cs-cv

arXiv:2603.17304v2 Announce Type: replace Abstract: Deep learning has become an important tool for Alzheimer's disease (AD) classification from structural MRI. Many existing studies analyze individual

A Controlled Audit of Architectural Complexity in Uncertainty-Aware Multi-Organ Ultrasound Classification

arXiv:2608.28063v1 Announce Type: new Abstract: Multi-organ ultrasound classifiers increasingly combine attention, mixture-of-experts routing, uncertainty gating, and evidential deep learning (EDL) ob

Anatomy-Aware Promptable Segmentation with Online Interactive Training for AUTOPET V

arXiv:2608.28461v1 Announce Type: new Abstract: We present an anatomy-aware, promptable model for whole-body lesion segmentation in FDG and PSMA PET/CT, developed for the AUTOPET V challenge. The prop

Can Tainted Pixels Expose Deepfake Videos?

arXiv:2608.27492v1 Announce Type: cross Abstract: Publicly-acceesible face-manipulation tools have made deepfake creation accessible to non-expert users. Against these, existing defenses are mostly po

Cut-ViT: Task-Specific Model Pruning via Gram Anchoring Subspace Consistency

arXiv:2608.28205v1 Announce Type: new Abstract: Pruning visual foundation models has attracted considerable attention. However, existing methods focus on rigid point-to-point token alignment on a sing

DART-FL: Burst-Aware Multitask Federated Learning under Dynamic Inference Demand at the Edge

arXiv:2608.27713v1 Announce Type: new Abstract: Edge intelligence systems increasingly require model training and online inference to coexist on resource-constrained devices, while inference demand ca

researcharxiv-cs-lg

DeicticVLA: Unifying Instruction Modes Based on Language and Deictic Gestures in a Single VLA

arXiv:2608.28108v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) allow users to specify manipulation tasks in natural language, but distinguishing a target or placement goal amon

FUSED: Forensic-Semantic Mixture-of-Experts for AI Inpainting Detection and Localization

model-releasesarxiv-cs-cv

arXiv:2608.28302v1 Announce Type: new Abstract: Diffusion-based inpainting models modify only a localized part of an image, while many AI-image detectors rely on global artifacts and do not localize.

Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2608.28375v1 Announce Type: cross Abstract: Global goodness-of-fit and discrepancy statistics can establish that a sample departs from a reference distribution without identifying which observat

Medical Imaging AI Competitions Lack Fairness

arXiv:2512.17581v2 Announce Type: replace Abstract: Benchmarking competitions are central to the development of artificial intelligence (AI) in medical imaging, defining performance standards and shap

Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity

arXiv:2511.07011v2 Announce Type: replace Abstract: Background: Remotely captured spoken language could provide objective, regular indicators of depression symptom severity. However, research to date

PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems

arXiv:2608.28378v1 Announce Type: new Abstract: Large language models are increasingly used as agentic workflow executors, yet existing training data and benchmarks largely assume informationally comp

Personalized and Multi-View Representation for Federated Cold-Start Recommendation

arXiv:2608.27826v1 Announce Type: cross Abstract: Federated recommendation (FedRec) enables personalized modeling without centralizing users' interaction histories, but most existing methods assume a

safetyarxiv-cs-lg

Predicting Turn-Taking Outcomes in Multi-Party Conversation: Interpretable Modelling of Speech and Gaze Dynamics with Interpersonal Closeness

arXiv:2608.27988v1 Announce Type: new Abstract: Smooth speaker transitions are fundamental to effective conversation and rely on an interlocutor's ability to predict when to enter the conversation. Th

Hardware

Quanta Perception as Probabilistic Events

arXiv:2608.27584v1 Announce Type: new Abstract: Autonomous systems rely on extracting information from light, yet remain brittle in extreme environments, from nighttime navigation to high-speed roboti

hardwarearxiv-cs-cv

Sledgehammer or Scalpel? A Fine-grained Adaptive Framework for Implicit Hate Speech

arXiv:2608.27462v1 Announce Type: new Abstract: Unlike explicit attacks with obvious profanity, implicit hate speech hides malice within seemingly compliant expressions through metaphors and contextua

Tutorials

Texture Image Classification Using DWT AlexNet Feature Fusion and Deep Neural Networks

arXiv:2608.28524v1 Announce Type: new Abstract: Texture image classification plays a significant role in computer vision applications, including industrial inspection, medical image analysis, remote s

tutorialsarxiv-cs-cv

The Instability of Safety: How Random Seeds and Temperature Expose Inconsistent LLM Refusal Behavior

arXiv:2512.12066v3 Announce Type: replace-cross Abstract: Current safety evaluations of large language models rely on single-shot testing, implicitly assuming that model responses are deterministic an

The persistence of painting styles

arXiv:2511.16695v2 Announce Type: replace Abstract: Art is a deeply personal and expressive medium, where each artist brings their own style, technique, and cultural background into their work. Tradit

When Tokenizers Fail: Byte-Level Chunking for Zero-Shot Transfer to Low-Resource Languages

arXiv:2608.27658v1 Announce Type: new Abstract: Subword tokenization hinders low-resource language processing by imposing frequency patterns from dominant languages onto script-sharing variants. Byte-

safetyarxiv-cs-cl

CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases

arXiv:2608.27391v1 Announce Type: new Abstract: LLMs are increasingly able to answer complex questions about enterprise-scale document collections. But evaluation is hard: companies don't want to shar

Decentralized Multitask Learning over Learned Task Graphs

arXiv:2608.26989v1 Announce Type: new Abstract: This paper investigates decentralized multitask learning over networks when the underlying task relationships are unknown. While existing graph-regulari

researcharxiv-cs-lg

DEEPCHART: How Far are LLMs from Faithful Data-Science Chart Generation?

arXiv:2608.26757v1 Announce Type: new Abstract: Faithful chart generation in real-world data-science workflows requires grounding visualizations in scattered evidence, computing chart-ready quantities

DocTalkBN: A Novel Dataset of Expert Telemedicine Conversations in Bengali

arXiv:2608.27110v1 Announce Type: new Abstract: Reliable medical conversational AI requires authentic expert--patient interaction data, yet such datasets remain scarce, especially for low-resource lan

Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learning

arXiv:2608.26901v1 Announce Type: cross Abstract: Automating prostate radiotherapy treatment planning is dosimetrically complex, particularly for extreme hypofractionated regimens. In this study, we i

EEG-to-Report: An Annotation and Feature-Text Framework for Training Language Models on Clinical EEG

arXiv:2608.26153v1 Announce Type: new Abstract: Clinical electroencephalography (EEG) reporting remains largely manual and time-consuming, and current EEG software ecosystems do not produce the struct

researcharxiv-cs-ai

Graph-Guided Selective Unlearning for Language Models: Controlling Support Routes Beyond Forget Seeds

arXiv:2608.26743v1 Announce Type: new Abstract: Enterprises fine-tune language models on proprietary data that may later require removal due to privacy, contractual, or compliance obligations. Selecti

GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts

arXiv:2509.25160v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly

Applications

Impressive new work from Google DeepMind showing real-world applications of agents for scientific research.

Impressive new work from Google DeepMind showing real-world applications of agents for scientific research. Impressive new paper from Google DeepMind. (bookmark it) It takes Co-Scientist out of simula

applicationsdair-ai--x

Invocation-Level Reliability of Tool-Using Agents

arXiv:2608.26189v1 Announce Type: new Abstract: Tool-using agents fail two ways: choosing the wrong tool, or forming wrong arguments, and an early failure of either kind can silently corrupt everythin

Applications

Multi-Image Visual Token Pruning in Large Visual Language Models

arXiv:2608.26806v1 Announce Type: new Abstract: With the growing demand for processing multiple image sequences in real-world applications, various visual token pruning methods have emerged to mitigat

applicationsarxiv-cs-cv

SHIFT: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval

arXiv:2606.18801v2 Announce Type: replace-cross Abstract: With the rapid expansion of massive multilingual corpora, Multilingual Information Retrieval (MLIR) has emerged as a critical technology for g

safetyarxiv-cs-ai

Local Ai

UniGeo: A Multi-modal Large Language Model for Text-Guided Cross-View Geo-Localization

arXiv:2608.26722v1 Announce Type: new Abstract: Text-guided drone geo-localization aims to identify a target region in a large-scale image gallery from a natural-language description. Existing methods

local-aiarxiv-cs-cv

Align Then Adapt: Label-Efficient Adapter Learning for Asymmetric Dense Retrieval

arXiv:2604.03403v2 Announce Type: replace-cross Abstract: Dense retrieval systems increasingly face an asymmetry between complex instruction-like queries and relatively simple, static document collect

Asymmetric Cross-Modal Fine-Grained Visual Categorization: ACF-Net and the BirdPro Benchmark

model-releasesarxiv-cs-cv

arXiv:2608.25520v1 Announce Type: new Abstract: Audio-visual cross-modal Fine-Grained Visual Categorization (FGVC) aims to identify fine-grained categories by jointly leveraging visual and auditory in

Automatic weld seam segmentation for industrial quality control: a comparison of RGB and polarimetric imaging with CNN and transformer architectures

arXiv:2608.25465v1 Announce Type: new Abstract: Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on the

b10660

model-releasesllama-cpp-releases

model: add Qwen3.8-Flash-Next (qwen4exp) (#27742) gguf: add qwen4exp (Qwen3.8-Flash-Next) arch and converter Adds the GGUF-side plumbing for HF model_type qwen4_exp: MODEL_ARCH.QWEN4EXP plus tensors f

BRIDLE: Generalized Self-supervised Learning with Quantization

arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu

DCEO: Direct Causal Effect Optimization for Long-Term User Value Modeling in E-commerce Search

arXiv:2608.25635v1 Announce Type: new Abstract: Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchand

safetyarxiv-cs-lg

Drift Variation Autoencoder: Unifying Generation and Representation Learning through Conditional Posterior Flow Matching

model-releasesarxiv-cs-lg

arXiv:2608.25138v1 Announce Type: new Abstract: Stochastic masking, cropping, or modality removal makes deterministic reconstruction an incomplete target: one observation can admit many clean completi

MLLMCLIP: Feature-Level Distillation of MLLM for Robust Vision-Language Representations

arXiv:2608.25575v1 Announce Type: new Abstract: Pretrained vision-language models such as CLIP excel at zero-shot recognition but often fail at compositionality, particularly attribute-object and rela

Overview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models

arXiv:2608.25662v1 Announce Type: new Abstract: In 2026, we held the fourth iteration of the SHROOM Shared Task series: SHROOM-Visions (extbf{S}hared-task on extbf{H}allucinations and extbf{R}elated e

PARAssist: A Framework for Personalized and Adaptive Robotic Assistance from Ambiguous User Requests

arXiv:2608.24905v1 Announce Type: cross Abstract: Service robots may encounter ambiguous user requests that require context-aware inference. Users may also have unique preferences with certain tasks w

researcharxiv-cs-ro

SelfGraphRAG: Bridging the Supervision Gap in Graph-Based RAG with Synthetic QA Generation

arXiv:2608.25123v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language models by incorporating external knowledge without retraining, but existing methods often u