Search: “papers”

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

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

DGX agent

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

7 Sept 2026

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

Jensen Huang says that AGI has been achieved. I strongly disagree. GPT-6 performs really well on benchmarks, including ARC-AGI-3. But benchm…

model-releasesgary-marcus--x

Jensen Huang says that AGI has been achieved. I strongly disagree. GPT-6 performs really well on benchmarks, including ARC-AGI-3. But benchmark performance is not the same as general intelligence. GPT

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,

KV cache as an agent runtime [R]

Our research team has been exploring an alternative approach to achieving interactivity and better responsiveness with LLM systems. One of the team members wrote up a post about it: https://research.y

agentsr-machinelearning

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

Lit Review on Benchmarking LLMs Running in your phone!: MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive and MCP-Augmented Environments

model-releasesr-localllama

Back to reading about LLMs as agents on your phone doing GUI tasks! This time I read about MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive and MCP-Augmented Environments a

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

LLM-guided program evolution improves 10 best-known circle-packing solutions (Packomania csqv, N=101-114) [R]

model-releasesr-machinelearning

I used an LLM to iteratively evolve an optimization algorithm rather than solve the packing directly. Starting from a simple seed solver, the LLM proposes algorithmic changes guided by a scoreboard of

Applications

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

Applications

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

Applications

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

researcharxiv-cs-lg

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

researcharxiv-cs-lg

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

When Financial Fine-tuning Fails: A Three-Level Detectability Analysis of Numerical Hallucination in Domain-Adapted Language Models

arXiv:2609.04806v1 Announce Type: new Abstract: Financial large language models are increasingly deployed for summarization of reports and disclosures, where numerical hallucination poses significant

researcharxiv-cs-ai

Tutorials

Why We Care About Understanding: Competence through Predictive Compression

arXiv:2609.04962v1 Announce Type: new Abstract: What is the relation between understanding and compression, and why does human understanding take such a heavily compressed form? Across information the

tutorialsarxiv-cs-ai

I read some strange criticisms of this post. So here is my take. I’m not fully endorsing the piece by Newport, but there’s quite some factua…

I read some strange criticisms of this post. So here is my take. I’m not fully endorsing the piece by Newport, but there’s quite some factually true information in it. Responsible and careful people (

safetygary-marcus--x

6 Sept 2026

GPT-6 is pretty good tbh

model-releasesemad-mostaque--x

GPT-6 is pretty good tbh @viktaur27 @Teslarati The rate of improvement from original GPT to GPT-3 is impressive. If this rate of improvement continues, GPT-5 or 6 could be indistinguishable from the s

5 Sept 2026

NInfer fork: 555k context@fp4 for 5090 with YARN, reliable kv host cacheing, monitoring, jinja, opened model support