Search: “papers”

DODR: Deterministic Operator-Driven Reasoning in Latent Space

model-releasesarxiv-cs-ai

arXiv:2609.04782v1 Announce Type: new Abstract: Autoregressive (AR) large language models formulate reasoning as token-level probabilistic sampling, which induces three fundamental defects in complex

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Dynamic Adaptation of the LLM Context for Generating Routines with Coupled Semantics

DGX agent

arXiv:2609.04570v1 Announce Type: cross Abstract: LLM-based code generation fails when correctness depends on execution-dependent coupling: the meaning of one routine is defined by the runtime behavio

agentsarxiv-cs-ai

7 Sept 2026

Local Ai

Encore: Infinite Audio-Video Generation with Adaptive Signal Routing

arXiv:2609.04249v1 Announce Type: cross Abstract: Existing audio-video generation methods produce well-synchronized clips but are limited to short durations, while long-video generation methods extend

local-aiarxiv-cs-cv

Enhancing Affine Maximizer Auctions with Correlation-Aware Payment

arXiv:2602.09455v2 Announce Type: replace-cross Abstract: Affine Maximizer Auctions (AMAs), a generalized mechanism family from VCG, are widely used in automated mechanism design due to their inherent

Enhancing Multimodal Emotion Recognition via Multi-Feature Encoding and Attention-Based Fusion

arXiv:2609.04690v1 Announce Type: cross Abstract: Multimodal emotion recognition has attracted growing interest due to its importance in human-computer interaction, remote education, and healthcare. T

applicationsarxiv-cs-ai

Evaluating Uncertainty and Quality of Vision-Language-Action-enabled Robots

arXiv:2507.17049v4 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA)-enabled robots integrate visual perception, natural language understanding, and action planning to interpret thei

researcharxiv-cs-ro

Explainable Clustering of Mixture Models

arXiv:2411.01576v3 Announce Type: replace Abstract: The explainable clustering problem was first posed by Moshkovitz et al. (ICML 2020) and studies how well an axis-aligned decision tree with K leaves

Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving

arXiv:2509.22480v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been widely used for problem-solving tasks. Most recent work improves their performance through supervised f

researcharxiv-cs-ai

From Plausible to Actionable: A Position on LLM Self-Explanations

arXiv:2607.15957v2 Announce Type: replace Abstract: Large Language Models (LLMs) can generate natural language explanations that rationalize their own decisions, a phenomenon commonly referred to as s

researcharxiv-cs-cl

Gradient-based Model Shortcut Detection for Time Series Classification

arXiv:2510.10075v2 Announce Type: replace-cross Abstract: Deep learning models have attracted lots of research attention in time series classification (TSC) task in the past two decades. Recently, dee

GUT: Quantifying and Optimizing the Reasoning Uncertainty of LLMs via Graph Complexity

arXiv:2609.05284v1 Announce Type: new Abstract: Recent years have witnessed great advances in the reasoning ability of Large Language Models (LLMs). However, the reasoning processes of LLMs often exhi

researcharxiv-cs-ai

How do LLMs Evaluate Perceived Moral Agency? Investigating Moral Decision-Making in Human-Artificial Agents Interactions

arXiv:2609.05037v1 Announce Type: cross Abstract: As LLMs take on roles requiring moral advice, understanding how they attribute moral agency becomes critical. Humans possess moral agency, the capacit

agentsarxiv-cs-ai

Human-Human & Human-Robot Interaction Transformer (H2INT) for Robot Navigation in Dense and Uncertain Crowds

arXiv:2609.05300v1 Announce Type: new Abstract: Safe robot navigation in dense crowds requires reasoning about pedestrian motion and how it may change in response to a robot. However, many learning-ba

safetyarxiv-cs-ro

Improving Language Identification for Code-Switched Utterances with Integer Linear Programming

arXiv:2609.05099v1 Announce Type: new Abstract: Automatic identification of code-switched (CS) utterances remains a challenge for language identification (LID) systems, causing such texts to be underr

researcharxiv-cs-cl

Intrinsic Temporal Adaptation of CLIP for Partially Relevant Video Retrieval

arXiv:2609.04800v1 Announce Type: new Abstract: Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos that contain moments relevant to a text query. Since the target moment occup

Local Ai

IPGeoAI: Transformer-Based Geolocation with LLM Semantic Fusion

arXiv:2609.04559v1 Announce Type: new Abstract: Accurate city-level IP Geolocation is an important enabler for the modern digital ecosystem, underpinning services ranging from local content delivery a

local-aiarxiv-cs-ai

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2609.04720v1 Announce Type: cross Abstract: Vision-language models (VLMs) are expected to respond helpfully to appropriate requests while withholding compliance with requests that are incorrect,

Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

arXiv:2609.05314v1 Announce Type: new Abstract: Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented docum

Learning 3D Editing without Paired Supervision via Generative Prior Distillation

arXiv:2609.04942v1 Announce Type: new Abstract: Instruction-guided 3D editing is essential for interactive content creation, yet it faces a significant bottleneck: the severe scarcity of high-quality

researcharxiv-cs-cv

LentEx: Generalizable Latent Entity Extraction via Synthetic Data and Instruction-Tuned LLMs

model-releasesarxiv-cs-cl

arXiv:2609.04511v1 Announce Type: new Abstract: Latent entity extraction (LEE) tackles the challenge of identifying implicit, contextually inferred entities within free text-an area where traditional

Leveraging Imperfect Restoration for Data Availability Attack

arXiv:2609.04627v1 Announce Type: new Abstract: The abundance of online data is at risk of unauthorized usage in training deep learning models. To counter this, various Data Availability Attacks (DAAs

LLM-Assisted Behavioural and Scenario Augmentation for Agent-Based Energy Adoption Models

arXiv:2609.04866v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) create opportunities to enrich simulation-based energy policy analysis, particularly by supporting struc

Long Horizon Transformer Quantile Fault Prediction for Multi Site Industrial Predictive Maintenance

arXiv:2609.04840v1 Announce Type: new Abstract: Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning wind

applicationsarxiv-cs-ai

LUMIN: Lightweight Universal Manufacturing Inspection Network for Anomaly Detection

arXiv:2609.04775v1 Announce Type: new Abstract: Industrial anomaly detection faces two engineering bottlenecks: memory bank construction latency and inference efficiency. Traditional sampling algorith

applicationsarxiv-cs-cv

Local Ai

MARLA: A Conceptual Scaffold for Regulatory Learning under the EU AI Act

arXiv:2609.04877v1 Announce Type: new Abstract: The EU AI Act positions regulation as part of the infrastructure for safe, trustworthy and market-ready innovation. Realising this ambition requires reg

local-aiarxiv-cs-ai

Model Retirement Creates Reproducibility Risk in Biomedical AI Publications

arXiv:2609.04699v1 Announce Type: new Abstract: Background. Large language models (LLMs) are being adopted in biomedical research at a rapid and accelerating pace, yet commercial services that host ma

agentsarxiv-cs-ai

Multi-scale Image Representation Compression

arXiv:2609.04274v1 Announce Type: cross Abstract: Overfitted codecs have demonstrated promising performance for image and video compression. In particular, for image compression, the Cool-chic family

Online Change-point Detection for Cooperative Multi-Agent Reinforcement Learning

arXiv:2609.05298v1 Announce Type: cross Abstract: Cooperative multi-agent reinforcement learning (MARL) systems rely on past experience for learning coordinated behaviour, but this experience may beco

agentsarxiv-cs-lg

Pack It My Way: Triadic Human-Robot Collaboration for Personalized Autonomous Packing

arXiv:2609.04620v1 Announce Type: new Abstract: Personalized autonomous packing requires robots to account for resident preferences that cannot be inferred from scene geometry alone. Expert teleoperat

agentsarxiv-cs-ro

Quantum-Assisted Memory-Efficient Training for Parameter-Intensive Wi-Fi-Based Human Activity Recognition

model-releasesarxiv-cs-lg

arXiv:2609.04271v1 Announce Type: new Abstract: Wi-Fi-based human activity recognition (HAR) has become an important part of integrated sensing and communications, paving the way for a range of contex

Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models

arXiv:2609.04714v1 Announce Type: cross Abstract: Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models s

Resilience Beyond Stationary Client Unavailability: Unlocking Efficient and Unbiased Federated Learning

model-releasesarxiv-cs-lg

arXiv:2609.04763v1 Announce Type: new Abstract: Due to resource constraints or external and internal uncertainties, clients in real-world federated learning systems are often intermittently available

Scalable Neural Video Representation Compression

arXiv:2609.04273v1 Announce Type: cross Abstract: Scalable video coding (SVC) encodes a video into a layered bitstream consisting of a base layer and one or multiple enhancement layers, enabling decod

researcharxiv-cs-cv

SCAPES: Semantically Conditioned Autoregressive Prior for Environmental Sounds

model-releasesarxiv-cs-ai

arXiv:2609.04634v1 Announce Type: cross Abstract: As generative audio models grow in complexity, the computational and ecological costs of synthesizing everyday sounds have become increasingly prohibi

Hardware

Self-Supervised Lexical Representation Learning for Fast, Large-Scale Phylogenetic Inference

arXiv:2609.05262v1 Announce Type: new Abstract: Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a global scale remains constrained by two fac

hardwarearxiv-cs-cl

Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling

arXiv:2601.18049v2 Announce Type: replace Abstract: Significant progress has been made in semi-supervised hyperspectral image (HSI) classification regarding feature extraction and classification perfo

SMILE: Self-Explainable Multimodal Information Bottleneck for Medical Diagnosis

arXiv:2609.05174v1 Announce Type: new Abstract: Explainability is increasingly seen as a crucial requirement in AI-based medical diagnosis, particularly in safety-critical clinical decision-making. Mo

safetyarxiv-cs-cv

Solving Hard XAI Queries Based on a Compiled Dual-Rail Encoding

arXiv:2609.04931v1 Announce Type: new Abstract: The widespread adoption of artificial intelligence (AI) within real-world applications has raised a lot of concerns regarding their trustworthiness, esp

applicationsarxiv-cs-ai

Temporal Residual Neural Radiance Fields for Monocular Video Dynamic Human Body Reconstruction

arXiv:2609.04984v1 Announce Type: new Abstract: In the field of computer vision and graphics, high-quality reconstruction of the human body in static scenes has been achieved in recent years by a sing

researcharxiv-cs-cv

Test-Time Adaptation via Cache Personalization for Facial Expression Recognition in Videos

arXiv:2603.21309v4 Announce Type: replace Abstract: Facial expression recognition (FER) in videos requires model personalization to capture considerable variation across subjects. Vision-language mode

The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures

arXiv:2410.23440v4 Announce Type: replace Abstract: Operator learning, the approximation of mappings between infinite-dimensional function spaces using machine learning, has gained increasing research

Think-Verify-Revise: Neuro-Symbolic Visual Reasoning with Vision-Language Models and Dynamic Logic Tensor Networks

arXiv:2609.05388v1 Announce Type: new Abstract: Visual reasoning tasks require a system to jointly perceive visual content and apply formal relational constraints---a combination that neither pure neu

ToPos: Automated Optimal Positioning on Topographic Manifolds using Constrained Geodesic Voronoi Decomposition

arXiv:2609.05084v1 Announce Type: new Abstract: Reliable autonomous mapping, environmental sampling, last-mile logistics, and infrastructure deployment depend on the optimal surface area-balanced dist

safetyarxiv-cs-ro

Toward Context-Aware Exoskeleton Assistance: Integrating Computer Vision Payload Estimation with a Multi-Metric Optimization Space

arXiv:2508.06207v3 Announce Type: replace Abstract: Back-support exoskeletons mitigate musculoskeletal strain, yet current systems rely on reactive sensing and lack context-aware assistance modulation

researcharxiv-cs-ro

Towards Efficient Parametric State Estimation in Circulating Fuel Reactors with Shallow Recurrent Decoder Networks

arXiv:2503.08904v3 Announce Type: replace Abstract: The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering syste

Tracing Audio Grounding and Answer Selection in Audio LLMs

arXiv:2609.04637v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) have advanced in audio understanding, yet they can still predict the answer by reasoning from textual cues or

researcharxiv-cs-ai

Hardware

Tuning Collective Patterns to Alleviate Congestion in Shared AI Clusters

arXiv:2609.04417v1 Announce Type: cross Abstract: Distributed AI training involves recurring rounds of data exchange between multiple pairs of GPU nodes. Slowdown in even one flow due to congestion ca

hardwarearxiv-cs-lg

What Matters in On-Policy Distillation? A Perspective on Data Efficiency and Data Selection

arXiv:2609.05198v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has emerged as a widely adopted post-training paradigm for enhancing large language models in reasoning domains. However, t