Search: “multimodal”

Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving

arXiv:2609.04070v1 Announce Type: new Abstract: Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a

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Distilling deep optical flow stereo methods to retrieve dense three-dimensional wind fields

DGX agent

arXiv:2609.03100v1 Announce Type: new Abstract: Geostationary atmospheric motion vectors (AMVs) provide the dense horizontal wind vectors (u,v) and heights ingested into data assimilation systems. Tra

researcharxiv-cs-lg

4 Sept 2026

Evaluating Large Language Models on Urdu Idioms

arXiv:2510.17460v2 Announce Type: replace Abstract: Idioms remain a persistent challenge in natural language processing due to their figurative and culturally grounded meanings, which distinguish them

Inferring Affective Consciousness in an Artificial Agent: A Case Study

arXiv:2609.03883v1 Announce Type: new Abstract: Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attracti

agentsarxiv-cs-ai

Learning to Zoom Efficiently with a Contrastive Curriculum

arXiv:2609.03206v1 Announce Type: cross Abstract: Using a zoom-in tool is an important foundational part of modern visual agents, because it allows to efficiently handle tasks involving high-resolutio

agentsarxiv-cs-cl

Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories

arXiv:2602.15154v2 Announce Type: replace Abstract: Reliable video understanding requires high-quality video datasets that can provide both precise semantic labels and temporally consistent annotation

researcharxiv-cs-cv

No country for old linguists: LLM-brain alignment underdetermines neural computation

arXiv:2609.03160v1 Announce Type: new Abstract: Nastase et al. (2026) argue that large language models (LLMs) may illuminate language processing because both rely on distributed, context-sensitive rep

Local Ai

OCR-EDR: Rendering-Aware Diagnosis and Repair for Closed-Loop OCR Improvement

arXiv:2609.03445v1 Announce Type: new Abstract: Although document OCR systems perform increasingly well on routine documents, complex formulas, structured text, and long-tail formats remain error-pron

local-aiarxiv-cs-cv

Applications

Opening mind by opening architecture: analysis strategies

arXiv:2609.03719v1 Announce Type: new Abstract: In numerical signal processing for electroacoustic composition, the progressive loss of specific development and research environments caused by the inc

applicationsarxiv-cs-cl

Pattern Over-Generalization of Knowledge Graph Embedding

arXiv:2609.03487v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) demonstrates its effectiveness for predicting missing links in knowledge graphs (KGs) by projecting entities and relat

ScoreMix: Synthetic Data Generation by Score Composition in Diffusion Models Improves Recognition

arXiv:2506.10226v3 Announce Type: replace-cross Abstract: Synthetic data generation is increasingly used in machine learning for training and data augmentation. Yet, current strategies often rely on e

Synthetic Semantic Supervision for Contrastive Code Representation Learning in Small Transformers: An Empirical Study

arXiv:2609.03702v1 Announce Type: new Abstract: General-purpose code embeddings power tools for code search, classification, and retrieval. Compact transformer encoders for code typically rely on eith

Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment

arXiv:2601.04736v2 Announce Type: replace Abstract: Despite remarkable capability in multi-modal understanding, deploying Multi-modal Large Language Models (MLLMs) in open-ended conversational scenari

Tree species mapping in Denmark: A comparison of spectral-temporal features with geospatial foundation model embeddings

arXiv:2609.03480v1 Announce Type: cross Abstract: We map tree species across Denmark using National Forest Inventory plots and EO data, while evaluating the potential of foundation models for large-sc

Unifying Conformal Language Tasks with In-Context Ensembles

arXiv:2609.03005v1 Announce Type: new Abstract: Many NLP tasks, such as summarization and extractive question answering, reduce to retrieving relevant content from documents under two constraints: cov

researcharxiv-cs-cl

Beyond Context Windows: Persistent Discovery Context for Data-Centric Agents

arXiv:2609.02129v1 Announce Type: new Abstract: Data-centric agents repeatedly perform a discovery step before planning or execution: identifying the data objects relevant to a task. Yet successful di

researcharxiv-cs-ai

Local Ai

Characterizing Text Branch Sensitivity in Medical Vision-Language Segmentation via Evidence Decoupling

arXiv:2609.02663v1 Announce Type: new Abstract: Pretrained vision-language models (VLMs) have shown promising performance in medical image segmentation by incorporating clinical text. However, it rema

local-aiarxiv-cs-cv

Contrastive Explanations in Quantitative Bipolar Argumentation Frameworks

arXiv:2609.02399v1 Announce Type: new Abstract: Argumentation frameworks are useful tools for representing and reasoning with information in a variety of settings, e.g. in supplementing AI models as t

Does Playing it Safe Count as Faithfulness? Reassessing LVLM Hallucination Mitigation Methods

arXiv:2609.01888v1 Announce Type: new Abstract: Recent inference-time hallucination mitigation methods for large vision-language models (LVLMs) report strong gains on hallucination benchmarks. However

From Detection to Characterization: A Large-Scale Study of Ragebait on Japanese X

arXiv:2609.02262v1 Announce Type: cross Abstract: Ragebait refers to online content intentionally designed to provoke anger or outrage and thereby increase attention and engagement. However, reliable

researcharxiv-cs-cl

OBJECTION! Lawyer Agents Mitigate Guilty Bias in Legal Judgment Prediction

arXiv:2609.02158v1 Announce Type: cross Abstract: Legal Judgment Prediction (LJP) models are typically trained on documents that describe facts from a prosecutorial perspective. Existing datasets furt

ProbeMatchDTI: Probe-Driven Multi-Scale Biochemical Pattern Matching for Drug-Target Interaction Prediction

arXiv:2609.02549v1 Announce Type: cross Abstract: Drug-target interaction (DTI) prediction is an important task in AI-driven drug discovery. Although recent biochemical representation learning methods

researcharxiv-cs-ai

Applications

RINSE: Robust Target-Time Normality Estimation for Zero-Shot Graph Anomaly Detection

arXiv:2609.02497v1 Announce Type: cross Abstract: Zero-shot graph anomaly detection seeks to deploy a detector trained on source graphs to unseen, unlabeled targets, yet domain shift can make source-d

applicationsarxiv-cs-ai

SALA: Semantic-Aware Logical Alignment for Complex Reasoning in In-Context Learning

arXiv:2609.02336v1 Announce Type: new Abstract: Effective in-context learning (ICL) for complex reasoning relies on selecting the right demonstrations. Traditional retrieval methods based on surface s

SignMatch: Matching Dictionary Signs to Continuous Sign Language Video

arXiv:2609.01886v1 Announce Type: new Abstract: The objective of this paper is to match dictionary sign videos to corresponding signs in continuous signing videos, where a match is defined by the visu

TalkFa: A Unified Benchmark for Farsi Dialogue Generation and Understanding

arXiv:2609.01810v1 Announce Type: new Abstract: Farsi, spoken by more than 120 million people, lacks a comprehensive benchmark for dialogue generation and understanding. We introduce TALKFA, a unified

A Dataset for Modeling Iterative Problem-Solving

arXiv:2609.00940v1 Announce Type: new Abstract: Solving problems through repeated attempts is a sequential modeling task: at each step, the solver receives feedback and decides how to revise their sol

A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data

arXiv:2609.01514v1 Announce Type: cross Abstract: Historically, retrieving rainfall data from satellite imagery has been the domain of space agencies. However, in recent years, the development of chea

researcharxiv-cs-cv

Tutorials

ADGNet: Asymmetric Dual-text Guided Network for Infrared Small Target Detection

arXiv:2609.00853v1 Announce Type: cross Abstract: InfRared Small Target Detection (IRSTD) is a challenging task. Relying solely on pixel-level information, vision-only methods struggle to distinguish

tutorialsarxiv-cs-ai

Beyond AHI: An Interpretable Causal-Discovery-Guided Framework for Sleep Recovery in Connected Health

arXiv:2606.18506v2 Announce Type: replace Abstract: Objective sleep assessment relies on polysomnography (PSG), yet clinical impact is often better reflected in patient-reported outcomes (PROs) such a

safetyarxiv-cs-lg

CoLT-Drive: Counterfactual Long-Tail Benchmarking and Knowledge-Preserving Adaptation for Driving Affordance Prediction

arXiv:2609.00242v1 Announce Type: cross Abstract: Long-tail autonomous driving failures are often framed as rare-object recognition errors. We argue that this view is incomplete: the decision-critical

CrossFeat: Bridging Imaging Modalities in Feature Descriptor Space

arXiv:2609.00272v1 Announce Type: new Abstract: Most advances in keypoint descriptions address monomodal settings, where image variations arise from viewpoint, illumination, or contrast changes. Multi

researcharxiv-cs-cv

Ctrl-F-Resist. Practices, Challenges, and Technical Needs of Civil Society Organizations Monitoring the Far-Right Online

arXiv:2609.00808v1 Announce Type: cross Abstract: As far-right actors increasingly exploit online platforms to disseminate ideology and mobilize supporters, civil society organizations (CSOs) play a v

Don't count out Gemini just yet. Feels like a new era of model releases. Models are so powerful that they now come with cyber variants. Love…

Don't count out Gemini just yet. Feels like a new era of model releases. Models are so powerful that they now come with cyber variants. Love the pricing on Gemini 3.8 Flash. Performance not bad. Gemin

model-releasesdair-ai--x

EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models

arXiv:2609.00479v1 Announce Type: new Abstract: For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and mo

From Legible to Inscrutable Trajectories: (Il)legible Motion Planning Accounting for Multiple Observers

arXiv:2602.09227v2 Announce Type: replace Abstract: In cooperative environments, such as in factories or assistive scenarios, it is important for a robot to communicate its intentions to observers, wh

agentsarxiv-cs-ro

Human-robot conversation with multiple participants in noisy public spaces

arXiv:2609.00648v1 Announce Type: new Abstract: For noisy real-world environments such as those in open public spaces, spoken dialogue systems for both autonomous robots and avatars should be carefull

agentsarxiv-cs-ro

Hypotheses-Guided Self Distillation for Continual Personalization

arXiv:2609.00251v1 Announce Type: new Abstract: As people increasingly interact with LLM assistants in daily life, continually adapting to individual preferences has become essential for effective lon

researcharxiv-cs-ai

In-Context Neurofeedback: Can LLMs Control Their Internal Representations through Privileged Access?

arXiv:2609.00904v1 Announce Type: new Abstract: Whether large language models (LLMs) can control their own internal representations matters for both machine metacognition and AI safety. A recent study

MemeBridge: A Dataset for Benchmarking and Mitigating the Bidirectional Cultural Gap in Meme Interpretation

arXiv:2609.00491v1 Announce Type: new Abstract: Communicating across cultures is inherently challenging, especially through culturally dense and ambiguous formats like memes. While people expect large

MobileOcc: A Human-Aware Semantic Occupancy Dataset for Mobile Robots

arXiv:2511.16949v2 Announce Type: replace-cross Abstract: Dense 3D semantic occupancy perception is critical for mobile robots operating in pedestrian-rich environments, yet it remains underexplored c

On the Design Fundamentals of Pixel Text Representation Learning

arXiv:2609.01147v1 Announce Type: cross Abstract: Text-rich visual inputs require models that can read, retrieve, and compress language directly in pixel space, yet existing pixel-text encoders strugg

Local Ai

Phrase-Localized Language-Contrastive Guidance: Training-Free Localized Accent Control for Code-Switching Text-to-Speech

arXiv:2609.01016v1 Announce Type: new Abstract: Current speech synthesis struggles with code-switching, which mixes a foreign language phrase into a primary language utterance, causing the phrase to b

local-aiarxiv-cs-cl

Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving

arXiv:2609.00111v1 Announce Type: new Abstract: We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of

RadMatch: Auditable Radiology Report Evaluation via Finding-Level Matching

arXiv:2609.01470v1 Announce Type: new Abstract: As AI systems are increasingly used to draft radiology reports, reliably evaluating their clinical quality remains a critical challenge. Large language

safetyarxiv-cs-cv

Reliability Challenges in Diffusion Vision-Language Models

arXiv:2609.01318v1 Announce Type: cross Abstract: Diffusion-based Large Vision-Language Models (dLVLMs) have recently emerged as a compelling alternative to autoregressive (AR) LVLMs, offering advanta

Socrates went Nuclear: Comparing Interaction Strategies for AI systems in a Learning Context using Brain Sensing

arXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud

SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-Image Generation

arXiv:2609.01582v1 Announce Type: new Abstract: Complex 3D spatial text to image generation requires models to convert natural language into stable visual geometry, not merely semantic appearance. Exi

safetyarxiv-cs-cv