Search: “models”

Understanding Cognition-Induced Risks in Agentic AI Systems

arXiv:2608.15304v1 Announce Type: new Abstract: Frontier agentic systems powered by large language models (LLMs) exhibit human-like patterns of cognition. As these systems become deeply integrated acr

agentsarxiv-cs-ai

Using the Mimi codec for metalinguistic representations

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DGX agent

arXiv:2608.15799v1 Announce Type: new Abstract: In this paper, we focus on the dictionary of 2048 tokens used in Mimi semantic token codebook, the neural codec of the Moshi language model. We show tha

researcharxiv-cs-cl

18 Aug 2026

What You Ask is What You Ground: Bridging Question Intent to Temporal Evidence for Grounded VideoQA

arXiv:2608.15708v1 Announce Type: new Abstract: We study a critical yet overlooked failure mode in Grounded Video Question Answering: question-invariant grounding, where models predict nearly identica

When Context Misleads: Intent-Guided Decoding for Robust Retrieval-Augmented Generation

arXiv:2608.16515v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves large language models by grounding generation in external evidence, but it also introduces a source trus

When Is an Agent Evaluation Over? Outcome Finality and Cross-Unit Separation

arXiv:2608.14940v1 Announce Type: new Abstract: Current agent evaluations score models on the state visible at the end of a stopped run which they count as one trial. However, interpreting the score a

agentsarxiv-cs-ai

When Uncertainty Isn't Enough: An Empirical Study of Self-Correction in Code Generation

arXiv:2608.14659v1 Announce Type: new Abstract: Large language models for code generation often produce incorrect solutions without reliable indicators of failure. We study whether uncertainty estimat

Zero-MELO: Test-Time Evidence Calibration with Multimodal LLMs for Zero-Shot Micro-Gesture Recognition

arXiv:2608.14854v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general video understanding, their capability in fine-grained and motion-centric tasks remains l

AgilePE: Autonomous UAV Pursuit-Evasion via Self-Play Reinforcement Learning

arXiv:2608.14135v1 Announce Type: cross Abstract: Autonomous pursuit-evasion is a fundamental challenge for Unmanned Aerial Vehicles (UAVs), requiring rapid decision-making under tightly coupled dynam

safetyarxiv-cs-lg

AppleScab-LT: A Longitudinal Real-Field Apple Scab Dataset for Temporal Disease Progression Analysis

arXiv:2608.14235v1 Announce Type: new Abstract: The development of reliable plant disease monitoring systems is constrained by limited longitudinal datasets capturing disease progression under natural

AtomBridge: Agentic VLA Inference Plugin for Long-Horizon Tasks in Scientific Experiments

arXiv:2602.09430v2 Announce Type: replace-cross Abstract: Robotic laboratories play a critical role in autonomous scientific discovery by enabling scalable, continuous experimental execution. Recent v

AutoSchema: Live Schema Grounding for Agentic Text-to-Sparql over Heterogeneous Knowledge Graphs

arXiv:2608.14228v1 Announce Type: new Abstract: Life science knowledge graphs make large collections of structured data available through SPARQL, but each resource uses its own schema, identifiers, an

agentsarxiv-cs-lg

CSG-Mamba: A Convolutional Scoring Gating Vision State Space Network for Endoscopic Polyp Segmentation

arXiv:2608.14146v1 Announce Type: new Abstract: Accurate polyp segmentation is critical for computer-aided colonoscopy, yet endoscopic images often contain low-contrast boundaries, mucosal texture int

Decoding the Past: An Uncertainty-Aware Deep Learning Framework for Sex Attribution in Prehistoric Hand Stencils

arXiv:2608.14539v1 Announce Type: cross Abstract: Determining the biological sex of the individuals who created Upper Paleolithic hand stencils remains a challenging problem due to the absence of grou

Designing Sustainable Federated Learning as a Service using Neural Architecture Search

arXiv:2608.14359v1 Announce Type: new Abstract: The sustainability constraints of FLaaS consumers pose significant challenges to maintaining carbon-feasible federated training in FLaaS environments. T

applicationsarxiv-cs-ai

EchoRec: Multi-Item Prediction-Empowered Generative Recommendation via Cycle-Consistent Preference Alignment

arXiv:2608.14011v1 Announce Type: cross Abstract: Generative recommendation autoregressively generates the semantic IDs of the target item, unifying preference modeling and index retrieval within the

GhostPoint: Self-Supervised Representation Learning by Hallucinating Occluded LiDAR Structure

arXiv:2608.14428v1 Announce Type: new Abstract: 3D object detection from LiDAR point clouds is a core problem in autonomous driving. Recent advances in self-supervised learning (SSL) enable scalable p

GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings

arXiv:2608.13698v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), often optimized with Group Relative Policy Optimization (GRPO), has become a central recipe for i

safetyarxiv-cs-cl

Hybrid Quantum-inspired Kolmogorov-Arnold Networks for Privacy-Aware Federated Biosignal Learning

arXiv:2608.13914v1 Announce Type: cross Abstract: Electrocardiogram (ECG) recordings are sensitive biomedical data, limiting the ability of hospitals and wearable devices to share raw signals for cent

Kolmogorov-Arnold Networks for Spatially Independent Multispectral Land Classification

arXiv:2608.13769v1 Announce Type: new Abstract: Land classification from satellite imagery is important for land management, environmental monitoring, and urban planning. Machine learning methods such

Label-Free Deep-Tissue Peripheral Nerve Detection with a Handheld Multimodal OCT Probe and NerveDetNet

arXiv:2608.13807v1 Announce Type: cross Abstract: Peripheral nerves buried beneath intact tissue are difficult to visualize during surgery and remain inaccessible to white light wide-field imaging and

Hardware

LatentAM: Real-Time, Large-Scale Latent Gaussian Attention Mapping via Online Dictionary Learning

arXiv:2602.12314v2 Announce Type: replace-cross Abstract: We present LatentAM, an online 3D Gaussian Splatting (3DGS) mapping framework that builds scalable latent feature maps from streaming RGB-D ob

hardwarearxiv-cs-cv

Learning Unsteady Aneurysm Hemodynamics with Physics-Informed DeepONets

arXiv:2608.13629v1 Announce Type: cross Abstract: Clinically actionable, patient-specific hemodynamic assessment, specifically wall shear stress, vortex structure and pressure distributions, is critic

researcharxiv-cs-lg

MINT: A Universal Zero-Shot Predictor for Transaction Data

arXiv:2608.14198v1 Announce Type: cross Abstract: Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalizatio

safetyarxiv-cs-cl

Multimarginal flow matching with optimal transport potentials

arXiv:2606.05327v2 Announce Type: replace Abstract: Flow matching (FM) has emerged as a powerful framework for learning dynamic transport maps between two empirical distributions. However, less explor

researcharxiv-cs-lg

OTIS: Learning High-Quality Time Series Features With Tiny Encoders

arXiv:2410.07299v3 Announce Type: replace-cross Abstract: We introduce OTIS, an open time series encoder that yields high-quality time series features for downstream deployment on any system, includin

applicationsarxiv-cs-ai

Participatory Moral AI Is Not Neutral: The Invisible Hand of Developers

arXiv:2608.14522v1 Announce Type: new Abstract: As AI systems make more morally loaded decisions across society, one response has been moral preference elicitation. In this approach, researchers poll

Quantum Multi-Armed Bandits and Linear Bandits: Lower Bounds and Algorithms

arXiv:2608.14319v1 Announce Type: new Abstract: We study quantum multi-armed bandits (QMAB) and quantum linear bandits (QLB) in the model of Wan et al. [2023], where the learner queries each arm or ac

safetyarxiv-cs-lg

SCVIB: Editable State-Conditioned Visual Instance Binding forMulti-Turn Personalized Localization

arXiv:2608.14148v1 Announce Type: new Abstract: We introduce editable state-conditioned visual instance binding, a multi-turn localization setting in which several support-defined instances are introd

Semantic Differentiation for Tackling Challenges in Watermarking Low-Entropy Constrained Generation Outputs

arXiv:2601.11629v2 Announce Type: replace-cross Abstract: We demonstrate that while the current approaches for language model watermarking are effective for open-ended generation, they are inadequate

researcharxiv-cs-lg

Shift Aware Transfer Learning with Adaptive Dual-Encoder Fusion for PM Forecasting in Data-Limited Environments

arXiv:2608.14456v1 Announce Type: new Abstract: Short-horizon forecasting of fine particulate matter (PM2.5) remains difficult when observations from the target domain are limited and the statistical

local-aiarxiv-cs-ai

SPARGen: Unifying Spatial Perception and Reasoning through Native Multimodal Generation

arXiv:2608.14138v1 Announce Type: cross Abstract: Spatial perception and reasoning from visual observations require recovering geometric structure, establishing correspondences, and understanding spat

The More Popular, The Harder to Forget: Adaptive Popularity for LLM Unlearning

arXiv:2608.14229v1 Announce Type: new Abstract: Popular facts are memorised more deeply during pretraining and resist removal longer than rare ones, yet existing LLM unlearning methods apply uniform g

local-aiarxiv-cs-cl

A Compositional Theory of Curvature in Probabilistic Circuits

arXiv:2608.12869v1 Announce Type: cross Abstract: Probabilistic Circuits (PCs) are generative models that support exact inference and, unlike deep neural networks, admit an exact and tractable measure

AmalthAI: An Open-Source Computer Vision Platform for Cultural Heritage

arXiv:2608.13343v1 Announce Type: new Abstract: Computer vision (CV) and machine learning (ML) offer new tools for cultural heritage (CH) artifact analysis, but the CV/ML pipeline remains largely inac

Attribute-Conditioned Multimodal Slot Factorization for Controllable Fashion Retrieval

arXiv:2608.12570v1 Announce Type: new Abstract: Fashion retrieval often requires satisfying multiple attributes at once, such as category, color, pattern, and demographic. Monolithic embeddings mix th

Better Decomposition, Free Aggregation: A Synthesizer-Folding Framework for Multilingual Multi-Hop Question Answering

arXiv:2608.13160v1 Announce Type: cross Abstract: Multilingual retrieval-augmented generation (mRAG) equips large language models with access to globally distributed external knowledge for complex mul

Beyond Handcrafted Security: Towards Self-Evolving Defense for LLM Agents

arXiv:2608.12977v1 Announce Type: cross Abstract: The expanding operational capabilities of large language model (LLM) agents introduce sophisticated security threats. Runtime defenses have emerged as

agentsarxiv-cs-ai

Beyond Simulated Benchmarks: Evaluating Motion Representations for Fall Detection Under Real-World Data Scarcity

arXiv:2608.13197v1 Announce Type: new Abstract: Falls are a major health concern for older adults, and wearable sensors have been widely explored for detecting falls and enabling timely intervention.

applicationsarxiv-cs-lg

CAPRI: Contract-Aware Proof Repair for Isabelle

arXiv:2608.13459v1 Announce Type: cross Abstract: We address the use of large language models (LLMs) to help discover Isabelle proofs. An Isabelle build establishes that the submitted theory is accept

'Cause' is Mechanistic Narrative within Scientific Domains: An Ordinary Language Philosophical Critique of 'Causal Machine Learning'

arXiv:2501.05844v4 Announce Type: replace Abstract: Causal Learning has emerged as a major theme of research in statistics and machine learning in recent years, promising computational techniques to r

applicationsarxiv-cs-lg

Tutorials

Class Geometry as Supervision for Sample-Efficient Open-World Detection

arXiv:2608.12698v1 Announce Type: new Abstract: Open-world object detection requires models to recognize known categories, reject unfamiliar objects, and incorporate new classes over time. This is esp

tutorialsarxiv-cs-cv

Communication Heterogeneity and Collective Consensus in Neural Cellular Automata

arXiv:2606.21202v2 Announce Type: replace-cross Abstract: Reaching global agreement from purely local interactions is a defining problem of collective intelligence, and most models of it assume that a

Tutorials

Continual Distillation Learning for Rehearsal-Free Class-Incremental Learning via Decoupled Prompting

arXiv:2407.13911v5 Announce Type: replace Abstract: Prompt-based continual learning has shown strong performance in rehearsal-free class-incremental learning by adapting learnable prompts while freezi

tutorialsarxiv-cs-cv

DAPD: Dual-Anchored Policy Distillation

arXiv:2608.01735v2 Announce Type: replace Abstract: On-policy (self) distillation (OPSD) is increasingly adopted for language-model post-training. It strengthens the teacher with privileged informatio

EgoPHI: Estimating Contact and Force from Egocentric Vision

arXiv:2608.13014v1 Announce Type: new Abstract: Understanding hand-object interaction from egocentric vision is essential for modeling how people physically engage with the surrounding world. Yet reas

applicationsarxiv-cs-cv

Hardware

Enhancing Virtual Agents through SLMs and Edge-Computing: An Exploratory Evaluation of Think and Memory Processes

arXiv:2608.13420v1 Announce Type: new Abstract: Embodied intelligent virtual agents are expected to operate as persistent, adaptive, and context-aware entities within complex virtual and Metaverse wor

hardwarearxiv-cs-ai

From Caveman to Expert Analyst: Energy Consumption of Variable LLM Tasks

arXiv:2608.12350v1 Announce Type: cross Abstract: The energy demand growth and environmental impacts of artificial intelligence (AI) have generated substantial interest in supplying sufficient low-cos

From Refuse to Richness: Rubric Rewards for Long-Form Hallucination Reinforcement Learning

arXiv:2608.12337v1 Announce Type: new Abstract: Rewards that penalize unsupported claims can improve grounding in long-form generation, but they can also teach models to answer less. We study this ref

researcharxiv-cs-cl