Search: “inference”

VLALight: Lightweight Vision-Language-Action Models for Emergency-Aware Traffic Signal Control

arXiv:2609.30709v1 Announce Type: cross Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretati

28 Sept 2026

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Applications

Werracle: Sub-Cent Intra-Block AI Reflex Oracles and Flash-Loan Circuit Breakers for EVM Smart Contracts

DGX agent

arXiv:2609.30719v1 Announce Type: cross Abstract: Contemporary on-chain artificial intelligence (AI) encounters an intractable Von Neumann memory and latency wall. Storing static floating-point neural

applicationsarxiv-cs-ai

28 Sept 2026

Where Compute Matters: Heterogeneous Attention for Efficient Video Diffusion

arXiv:2609.31050v1 Announce Type: new Abstract: Efficient video generation requires reducing the quadratic cost of self-attention over long spatio-temporal token sequences. Existing efficient-attentio

28 Sept 2026

A Fast and Effective Solution to the Problem of Look-ahead Bias in LLMs

arXiv:2512.06607v2 Announce Type: replace-cross Abstract: Applying LLMs to predictive tasks in finance is challenging due to look-ahead bias resulting from their training on long time-series data. Thi

safetyarxiv-cs-cl

A Living Benchmark for Information Retrieval from Electronic Health Records

arXiv:2609.30205v1 Announce Type: new Abstract: Large language model (LLM)-based clinical assistants are increasingly being integrated into electronic health record (EHR) systems, transforming how cli

A Rapid Pipeline for Training and Deploying ML Models on WeBe Band

arXiv:2609.29084v1 Announce Type: new Abstract: Developing optimized machine-learning algorithms for edge devices with limited computational and memory resources is challenging, time-consuming, and hi

local-aiarxiv-cs-ai

A Vision-Language Framework for Measuring Social Life on Sidewalks

arXiv:2609.28476v1 Announce Type: cross Abstract: While a number of methods exist for counting pedestrians in street-view imagery, these mostly ignore the social dimensions of pedestrian activity. A s

researcharxiv-cs-cv

Agents

Agentic Detection of Online Conspiracies

arXiv:2609.30250v1 Announce Type: new Abstract: Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express

agentsarxiv-cs-cl

An Explainable DistilBERT-BiLSTM-Attention Framework for Binary and Multi-Class Hate Speech Detection

arXiv:2609.28703v1 Announce Type: cross Abstract: Hate speech on social media poses serious risks to social harmony, mental well-being, and public safety, making its timely and accurate detection esse

Agents

ASIRF: An Agentic Framework for Context-Dependent Sensitive Information Redaction

arXiv:2609.29191v1 Announce Type: new Abstract: Sensitive information is defined by domain and intent, not a universal category, yet redaction systems such as privacy filters and named-entity recogniz

agentsarxiv-cs-ai

Beyond Feature Reliability: Repeat-Informed Multifractal Curve Regression for Brain-Age Prediction

arXiv:2609.29307v1 Announce Type: new Abstract: Brain-age prediction from resting-state fMRI provides a quantitative framework for characterizing age-related changes in spontaneous brain dynamics and

Beyond Model Size: Redesigning LiSenNet for embedded speech enhancement

model-releasesarxiv-cs-lg

arXiv:2609.29866v1 Announce Type: cross Abstract: Deploying real-time speech enhancement on resource-constrained devices requires meeting strict latency, memory, and energy constraints. Microcontrolle

BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion

arXiv:2609.29487v1 Announce Type: new Abstract: Knowledge graph completion models optimize ranking, although many downstream applications require calibrated probabilities. We present BLADE, a variatio

CataOPD: Catalytic On-Policy Distillation for Large Language Model Reasoning

arXiv:2609.29518v1 Announce Type: new Abstract: Reinforcement learning (RL) and on-policy distillation (OPD) are two representative paradigms for improving large language model reasoning. However, whe

safetyarxiv-cs-lg

Comparing YOLOv11 and YOLOv8 for instance segmentation of occluded and non-occluded immature green fruits in complex orchard environment

arXiv:2410.19869v4 Announce Type: replace Abstract: This study conducted a comprehensive performance evaluation on YOLO11 (or YOLOv11) and YOLOv8, the latest in the 'You Only Look Once' (YOLO) series,

researcharxiv-cs-cv

DAWN: Noise-Robust Quadruped Parkour via Depth-Denoising World Models

arXiv:2609.29092v1 Announce Type: cross Abstract: Vision-based legged locomotion methods assume clean depth at training time and rely on hand-tuned post-processing filters at deployment. However, filt

DCRMTA: Deep Causal Representation Learning for Multi-Touch Attribution

arXiv:2401.08875v3 Announce Type: replace-cross Abstract: Multi-touch attribution (MTA) is essential for estimating the contribution of individual advertising touchpoints to user conversions. While re

Design and Evaluation of LLM Chaining-Based Task Planning for General Purpose Service Robots

arXiv:2609.29043v1 Announce Type: cross Abstract: General Purpose Service Robot (GPSR) tasks, as defined in the RoboCup@Home benchmark, require robots to interpret diverse natural language commands an

Edge AI on Constrained Devices for Binary Sleep-Wake Classification in Dynamic Environments

arXiv:2609.29163v1 Announce Type: new Abstract: This paper presents an Edge AI-based system for detecting sleep and wake states in non-stationary mobile environments using resource-constrained embedde

local-aiarxiv-cs-lg

Efficient Continuous DEM Reconstruction under Limited Target-Resolution Supervision

arXiv:2609.29864v1 Announce Type: new Abstract: High-resolution digital elevation models (DEMs) support Earth observation applications, but paired training references are often available only at coars

local-aiarxiv-cs-cv

Tutorials

Evaluation of OpenAI o1: Opportunities and Challenges of AGI

arXiv:2409.18486v5 Announce Type: replace Abstract: This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, sp

tutorialsarxiv-cs-cl

Foundations of Large Language Models

arXiv:2501.09223v3 Announce Type: replace-cross Abstract: This is a book about large language models. As indicated by the title, it primarily focuses on foundational concepts rather than comprehensive

From Prediction to Explainable Provider Behavior Profiles for Fraud, Waste, and Abuse Review

arXiv:2609.28477v1 Announce Type: cross Abstract: Claims data can show that provider behavior changed but cannot by itself explain why. FWA (fraud, waste, and abuse) review requires identifying materi

Tutorials

Generative Atmospheric Super-Resolution from Heterogeneous In Situ Observations through Composable Interfaces

arXiv:2609.29027v1 Announce Type: new Abstract: Atmospheric observations are sparse, heterogeneous, and unevenly distributed, whereas many generative atmospheric models learn distributions over regula

tutorialsarxiv-cs-lg

Hardware

GHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS

arXiv:2609.29999v1 Announce Type: cross Abstract: Post-training quantization of vision--language models (VLMs) is typically assessed through aggregate task accuracy and memory savings, but preserving

hardwarearxiv-cs-ai

Grow the Harness, Not the Context: From Strategy-Free Scaffolds to Reusable Specialist Agents

arXiv:2609.26760v2 Announce Type: replace Abstract: Large language model (LLM) agents often handle streams of related tasks, yet standard harnesses repeatedly ask the model to reconstruct the same con

Human-AI-Powered Hypothesis Testing: Cost-Aware Selective AI Scoring and Sequential Human Escalation

arXiv:2609.28859v1 Announce Type: new Abstract: Large language models are increasingly used as inexpensive judges to evaluate outputs, label data, and assess whether a system meets a desired quality s

Image Fidelity is Not Field Fidelity: Joint Thermodynamic Reconstruction and Error Localization in Neural Tomography

arXiv:2609.28868v1 Announce Type: new Abstract: Neural fields for scientific tomography are optimized from 2D images, but the actual quantity of interest is often a latent 3D physical field. Because t

local-aiarxiv-cs-lg

Jev-Mobile: Jev as an Executor for Mobile GUI Agents

arXiv:2609.30186v1 Announce Type: new Abstract: Vision-language models (VLMs) have become a common foundation for autonomous mobile GUI agents, but most existing systems rely on the VLM for both plann

local-aiarxiv-cs-ai

Agents

LabFactory: Building and Evaluating Executable AI Labs

arXiv:2609.28697v1 Announce Type: new Abstract: Scientific tasks specify a desired capability, but realizing it often requires building a computational system tailored to the task---acquiring data, de

agentsarxiv-cs-lg

LeafTrackNet: A Deep Learning Framework for Robust Leaf Tracking in Top-Down Plant Phenotyping

arXiv:2512.13130v2 Announce Type: replace Abstract: High-resolution phenotyping at the level of individual leaves offers fine-grained insights into plant development and stress responses. However, the

Learning Better Reasoning for Generative Recommendation with Semantic IDs

arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user'

Learning from Mixed-Quality Deployment Experience for Robot Manipulation

arXiv:2609.29000v1 Announce Type: new Abstract: Robot policies deployed in real environments naturally accumulate mixed-quality experience, including successful executions, partial progress, and failu

safetyarxiv-cs-lg

Long-Tail Adaptive Flow Matching with Explicit Conditional Consistency Guidance for Precise Multimodal Face Synthesis

arXiv:2609.29581v1 Announce Type: new Abstract: Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptim

safetyarxiv-cs-cv

Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their

M-plicits: Neural Implicit Surfaces via Nested Multiscale Residuals

arXiv:2609.28684v1 Announce Type: new Abstract: Encoding input coordinates with sinusoidal functions into multi-layer perceptrons (MLPs) has proven effective for implicit neural representations (INRs)

M^2PFN: End-to-End Disentangled Alignment for Generalizable Multimodal In-Context Learning in Alzheimer's Disease

arXiv:2609.28836v1 Announce Type: cross Abstract: While various multimodal methods combining imaging and tabular data for Alzheimer's disease (AD) diagnosis were proposed, they are often limited in ge

MILO: Efficient Many-shot In-Context Learning with Block-wise Low-rank Compression

arXiv:2609.29913v1 Announce Type: new Abstract: Many-shot in-context learning (ICL) enables large language models (LLMs) to adapt to complex tasks by conditioning on thousands of demonstration example

local-aiarxiv-cs-cl

Mind What Matters for Reasoning: Aligning Cross-Modal Attention via Selective Probability Mass Concentration

arXiv:2609.29940v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) achieve strong performance on visual reasoning tasks, yet remain prone to hallucinations and over-reliance on

Modelling dynamic systems transfer functions from events in computational neuromorphic imaging

arXiv:2609.29863v1 Announce Type: new Abstract: Event Vision Sensing (EVS) report threshold crossings of log-irradiance, so a static optical system imaging a static scene produces no output at all. Th

researcharxiv-cs-cv

Monitoring Urban Traffic Dynamics at Fine Spatiotemporal Resolution Using Distributed Acoustic Sensing and Deep Learning

arXiv:2609.28793v1 Announce Type: new Abstract: Mapping the distribution of traffic dynamics at high spatiotemporal resolution is a fundamental question in transportation research. Distributed acousti

MORE-PLR: multi-output regression employed for partial label ranking

arXiv:2609.29386v1 Announce Type: new Abstract: The partial label ranking problem is a supervised learning scenario that aims to fit a preference model that predicts a bucket order defined over a set

MultiwayPAM: Multiway Partitioning Around Medoids for LLM-as-a-Judge Score Analysis

arXiv:2603.10287v2 Announce Type: replace-cross Abstract: LLM-as-a-Judge is a flexible framework for text evaluation, which allows us to obtain scores for the quality of a given text from various pers

safetyarxiv-cs-lg

Named Entity Recognition using Sliding Window Approach

arXiv:2609.29682v1 Announce Type: new Abstract: Named Entity Recognition (NER) is a core NLP task, but transformer-based sentence-level models struggle with long documents because of fixed input-lengt

researcharxiv-cs-cl

Tutorials

Neuro-symbolic AI for Industrial Configuration

arXiv:2609.29947v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive performance on a wide range of generative tasks. Yet their probabilistic nature makes them, in isolat

tutorialsarxiv-cs-ai

NNV3: Expanding Neural Network Verification to New Architectures and Domains

arXiv:2609.30050v1 Announce Type: new Abstract: We present NNV3, the latest version of the Neural Network Verification (NNV) tool, a MATLAB framework for formal verification of deep learning models an

Path-specific harm decomposition: A partial identification framework

arXiv:2609.29938v1 Announce Type: cross Abstract: A central goal when designing treatment policies is often to 'do no harm', that is, to avoid interventions that improve average outcomes while worseni

Pistis Technical Report

arXiv:2609.28554v1 Announce Type: new Abstract: We introduce the Pistis model family, comprising 27B- and 9B-parameter multimodal large language models built on Qwen3.6 and Qwen3.5, respectively, and