Search: “multimodal”

ProtoRAG: Prototype-Based Retrieval Augmentation for Few-Shot Fine-Grained Remote Sensing Object Detection

arXiv:2609.05953v1 Announce Type: new Abstract: Few-shot fine-grained object detection (FGOD) in remote sensing imagery is challenging because limited annotations must support both object localization

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Safety

REVA-PO: Stabilizing Reinforcement Learning for Chest X-ray Report Generation

DGX agent

arXiv:2607.10147v2 Announce Type: replace Abstract: Automated chest X-ray report generation has recently benefited from reinforcement learning (RL) and large language models. However, RL training ofte

safetyarxiv-cs-cv

9 Sept 2026

Self-Supervised Multi-View 3D Gaze Target Estimation via Probabilistic Ray Marching

arXiv:2609.07415v1 Announce Type: new Abstract: We present a self-supervised approach, Self-MVGTE, for estimating 3D gaze targets from multiple camera views. Unlike existing methods that independently

SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models

arXiv:2609.05533v1 Announce Type: new Abstract: Long-horizon manipulation is partially observable: the information needed to choose the next action may appear only in observations from minutes earlier

safetyarxiv-cs-cv

SoftRerank: Hierarchical Soft Fusion with Candidate-Label Reranking for Long-Tailed Micro-Action Recognition

arXiv:2609.08221v1 Announce Type: new Abstract: Micro-actions are subtle, low-intensity non-verbal behaviors that provide cues to fine-grained human states, including emotions and intentions. Recogniz

Solution for UCF UrbanTwin LUMPI Track: Sim-to-Real Urban LiDAR 3D Object Detection

arXiv:2609.07590v1 Announce Type: new Abstract: We present our solution to the LUMPI track of the UCF UrbanTwin Sim2Real LiDAR Challenge at the 6th DriveX Workshop, ECCV 2026. The detector must be tra

SynthRCT: Scalable Conditional Deformation Synthesis for Synthetic Repeat CT Generation

arXiv:2609.08627v1 Announce Type: new Abstract: In proton therapy, plans are typically optimized on a single planning CT, making robustness evaluation essential under anatomical changes. However, curr

Time-Aware Assistive Navigation

arXiv:2609.05596v1 Announce Type: new Abstract: Can interactive vision-and-language agents learn not just what to say but also extbf{extit{when}} to say it? Current language models rarely plan over wh

Applications

Toward Robust Single-Photon Perception for Robots: A Condition-Aware Active Learning Approach

arXiv:2505.04376v2 Announce Type: replace-cross Abstract: LiDAR-based perception plays a fundamental role in modern robotic systems for environment understanding and navigation. Single-photon LiDAR (S

applicationsarxiv-cs-cv

Unexplored flaws in multiple-choice VQA make benchmarking unreliable

arXiv:2511.22341v2 Announce Type: replace Abstract: Previous works identify sensitivity to option order as a key issue in multiple-choice VQA (MC-VQA) evaluation and propose protocols to mitigate this

Uni-Inter: Unifying 3D Human Motion Synthesis Across Diverse Interaction Contexts

arXiv:2511.13032v2 Announce Type: replace Abstract: We present Uni-Inter, a unified framework for human motion generation that supports a wide range of interaction scenarios: including human-human, hu

Unified Vision-Centric Pedestrian Crossing Action Prediction via Adaptive Patch Projection and Proactive Spatial Rectification

arXiv:2609.07420v1 Announce Type: new Abstract: Vision cues are available and informative for pedestrian action prediction, but obtaining stable target-centric representations from video frames remain

Visual Search Augmented Chain-of-Thought Reasoning for Attribute Value Extraction from Product Videos

arXiv:2609.06410v1 Announce Type: cross Abstract: Existing approaches to visual attribute value extraction (AVE) primarily rely on static product images, failing to capture temporal cues, multi-angle

WeaveLA: Event Driven Cross-Subtask Latent Memory Weaving for Repetitive Robot Manipulation

arXiv:2606.17463v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) policies have achieved remarkable single-step manipulation, yet they remain brittle precisely where each stage depends

safetyarxiv-cs-cv

What Are You Doing? A Closer Look at Controllable Human Video Generation

arXiv:2503.04666v2 Announce Type: replace Abstract: High-quality benchmarks are crucial for driving progress in machine learning research. However, despite the growing interest in video generation, th

VISTA: Dense Multi-Label Classroom Coding with Vision-Language Models

arXiv:2609.04550v1 Announce Type: new Abstract: Video-language benchmarks are usually constructed by the dataset authors without published reliability statistics, leaving the noise floor of the constr

7 Sept 2026

Agents

A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms

arXiv:2609.04170v1 Announce Type: new Abstract: Multi-agent AI science ecosystems rely on agents possessing tools that allow them to communicate, coordinate, and build on each other's work. Yet this s

agentsarxiv-cs-ai

Analysis of Prompt Engineering for Drug Toxicity Prediction

arXiv:2609.03635v1 Announce Type: new Abstract: Clinical trials in the UK can cost up to {pounds}1.3 million, with approximately 90% drug failure rate. Toxicity is a major contributing factor in drug

researcharxiv-cs-ai

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

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

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

Evaluating Large Language Models on Urdu Idioms

model-releasesarxiv-cs-cl

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

Agents

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

Agents

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

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

safetyarxiv-cs-cl

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

model-releasesarxiv-cs-ai

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

model-releasesarxiv-cs-ai

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

safetyarxiv-cs-cl

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

model-releasesarxiv-cs-ai

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

model-releasesarxiv-cs-cl

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

model-releasesarxiv-cs-cl

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

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