Search: “papers”

AIBL: Augmented Instance-Based Learning with Structured Memory and Neural Embeddings

arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over

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AIGS: Adaptive Incremental Gating System for Online Representation Learning in Non-Stationary Data Streams

DGX agent

arXiv:2610.02661v1 Announce Type: new Abstract: Real-time data streams in Web of Things (WoT) and edge computing environments often evolve through latent regime changes. For online representation lear

model-releasesarxiv-cs-lg

5 Oct 2026

ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling

arXiv:2602.09009v2 Announce Type: replace-cross Abstract: Scaling network depth has been a central driver behind the success of modern foundation models, yet recent investigations suggest that deep la

Balancing Multimodal Learning via Functional Progress

arXiv:2610.03035v1 Announce Type: new Abstract: Multimodal learning often suffers from modality imbalance, where the joint optimization process is dominated by a single modality. Existing methods typi

Beyond Entropy: Self-Diagnostic Multi-Role Token Optimization for Video Reasoning

arXiv:2610.03400v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has substantially advanced multimodal reasoning, yet it remains fundamentally limited by ambiguous token-

local-aiarxiv-cs-cv

Can We Trust LLMs on Memristors? Diving into Reasoning Ability under Non-Ideality

arXiv:2603.13725v2 Announce Type: replace Abstract: Memristor-based analog compute-in-memory (CIM) architectures provide a promising substrate for the efficient deployment of Large Language Models (LL

researcharxiv-cs-cl

Applications

Capturing Dynamics: The 4D Facial Expression Intensity Dataset

arXiv:2610.02647v1 Announce Type: new Abstract: The estimation and analysis of facial expression intensity play a crucial role in affective communication and human-computer interaction. Previous resea

applicationsarxiv-cs-cv

Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents

arXiv:2610.02330v1 Announce Type: new Abstract: Large language models (LLMs) rely on long-horizon tool invocation sequences for complex tasks, where each invocation can alter the task state and condit

agentsarxiv-cs-ai

Closing the Train-Test Gap in World Models for Gradient-Based Planning

arXiv:2512.09929v2 Announce Type: replace Abstract: World models paired with model predictive control (MPC) can be trained offline on large-scale datasets of expert trajectories and enable generalizat

Constraint-Aware Training

model-releasesarxiv-cs-lg

arXiv:2610.02909v1 Announce Type: new Abstract: When generating programs with language models, constrained decoding can apply program analyses to exclude tokens that violate syntax, scope, or typing r

Credit Where It Matters: Dependency-Aware Policy Optimization for Terminal Agents

arXiv:2610.03634v1 Announce Type: new Abstract: Terminal-using agents benefit from reinforcement learning (RL) in coding, debugging, and other multi-step terminal tasks. In these tasks, later commands

safetyarxiv-cs-ai

CRISP: A Framework for Clause-Reconstructed Interpretable NeuroSymbolic Propositions

arXiv:2610.02431v1 Announce Type: new Abstract: Deep neural networks achieve high accuracy through layered numerical transformations, yet their decisions remain difficult to audit because decision evi

CVE2AP: Automated Generation of PDDL-Encoded Attack Paths via Large Language Models

model-releasesarxiv-cs-ai

arXiv:2610.03383v1 Announce Type: new Abstract: Attack Path (AP) modeling is fundamental to cybersecurity analysis, where the Planning Domain Definition Language (PDDL) has been widely adopted to enco

Decoding the Functional Roles of Register and High-Norm Patch Tokens in Vision Transformers

arXiv:2610.03698v1 Announce Type: new Abstract: Self-supervised Vision Transformers (ViTs), such as DINOv2, learn rich visual representations, but the functions of their internal tokens remain poorly

tutorialsarxiv-cs-cv

Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling

arXiv:2512.19905v3 Announce Type: replace-cross Abstract: Recent developments in large language models have shown advantages in reallocating a notable share of computational resource from training tim

Depth Hypothesis Guided Iterative Refinement for Event-Image Monocular Depth Estimation

arXiv:2610.03439v1 Announce Type: new Abstract: Event cameras hold excellent dynamic properties, showing great potential for monocular depth estimation (MDE). However, existing methods mainly improve

local-aiarxiv-cs-cv

Differential Privacy as a Perk: Federated Learning over Multiple-Access Fading Channels with a Multi-Antenna Base Station

arXiv:2510.23463v4 Announce Type: replace Abstract: Federated Learning (FL) is a distributed learning paradigm that preserves privacy by eliminating the need to exchange raw data during training. In i

local-aiarxiv-cs-lg

Distributionally Robust Survival Models under Subpopulation Shift and Outlier Contamination

arXiv:2610.02868v1 Announce Type: cross Abstract: Learning robust survival models under distribution shift is an important but challenging problem in many applications. In heterogeneous populations, a

Estimating prevalence with precision and accuracy

arXiv:2507.06061v2 Announce Type: replace-cross Abstract: Unlike classification, whose goal is to estimate the class of each data point, quantification (or prevalence estimation) aims to estimate the

Evaluating LLM-as-a-Judge Beyond Score Alignment: A Psychometric Analysis of Residual Judging Difficulty

arXiv:2610.02877v1 Announce Type: new Abstract: Large language models (LLMs) are widely used as automatic judges, with validity typically assessed via alignment with human scores. However, aggregate a

safetyarxiv-cs-cl

Exploring the Trade-Off Between Structured Pruning and Fault Tolerance in Deep Neural Networks for Space Applications

arXiv:2610.03117v1 Announce Type: new Abstract: Deep Neural Networks (DNNs) inherently exhibit a degree of robustness to bit-level faults due to their distributed representation of information. As a m

ForestQuery: Boundary-Aware and Spatially Anchored Query Learning for Unified Forest Point Cloud Segmentation

arXiv:2610.03403v1 Announce Type: cross Abstract: Forest point cloud segmentation is fundamental for fine-grained 3D forest scene understanding, yet remains challenging due to irregular tree structure

tutorialsarxiv-cs-ai

Generalization of Transformer-Based Neural Quantum States via In-Context Learning

arXiv:2610.03463v1 Announce Type: cross Abstract: Neural quantum states based on modern deep learning architectures have emerged as powerful representations for quantum many-body systems. In particula

Applications

High-Dimensional Asymptotics and Dataset Selection for Private Transfer Learning

arXiv:2610.02578v1 Announce Type: cross Abstract: To commit to buying external data or participate in collaborative learning, one must decide whether the additional data will improve prediction enough

applicationsarxiv-cs-lg

How Robust Is Multimodal Claim Verification to LLM Rewriting?

arXiv:2610.02841v1 Announce Type: new Abstract: LLMs are known to introduce stylistic changes into generated text, yet how these stylistic shifts affect model decisions on scientific tasks remains und

researcharxiv-cs-cl

How to Have a Sensitive Debate: An Instance-Optimal Protocol for AI Debate

arXiv:2610.02557v1 Announce Type: new Abstract: As powerful AI systems reach and sometimes surpass the abilities of human experts across a range of cognitively demanding tasks, the problem of accurate

tutorialsarxiv-cs-ai

Interpretable Deepfake Detection in Videos via Explicit Forensic Features and Temporal Modeling

model-releasesarxiv-cs-cv

arXiv:2610.03380v1 Announce Type: new Abstract: Deepfake detection in videos remains challenging, as manipulated content may appear visually consistent at the frame level while exhibiting subtle tempo

Joint Movement and Compression Ratio Design for Mobile Embodied AI Networks (MEAN)

arXiv:2610.02334v1 Announce Type: cross Abstract: Mobile embodied AI networks (MEAN) enable embodied agents to perceive, reason, communicate, and act in wireless environments. In such networks, agent

agentsarxiv-cs-lg

Learn Feasibility Once, Optimize All Objectives: Derivative-Free Diffusion Models for Chance-Constrained Programming

arXiv:2610.03071v1 Announce Type: new Abstract: Chance-constrained programs (CCPs) optimize decisions under uncertainty by limiting the probability of constraint violation. Despite advances in traditi

tutorialsarxiv-cs-lg

Lessons learned while building Apex-2

model-releasesr-localllama

Hi everyone, thank you so much for all the interest in my model. It's more than I expected. Here is a short summary of the trial and error I went through while building Apex-2. 1. GPUs were always the

MACTS-EM: Multi-Agent Collaborative Time Series Forecasting with Emergent Memory

arXiv:2610.02255v1 Announce Type: new Abstract: Time series forecasting remains a critical challenge across numerous domains. Despite significant advancements, existing approaches struggle with comple

agentsarxiv-cs-lg

MiDShip: Multimodal Dataset of Ship Cargo Hold Structures for Engineering Design

model-releasesarxiv-cs-lg

arXiv:2610.02214v1 Announce Type: cross Abstract: Ship structures govern vessel strength, safety, and manufacturability, but their design must satisfy hundreds of classification society requirements,

Mitigating Private Data Leakage in LLMs with Whiteout

arXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible websit

safetyarxiv-cs-ai

Morpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish

arXiv:2606.18717v2 Announce Type: replace-cross Abstract: Turkish is agglutinative: meaning is carried by morphemes, yet the subword tokenizers that drive modern language models split words by corpus

safetyarxiv-cs-ai

Multi-Modal Environment-Aware Beam Management for Massive MIMO: A Geometry-Driven Virtual Base Station Framework

arXiv:2606.26567v1 Announce Type: cross Abstract: High-frequency massive multiple-input multiple-output (MIMO) systems promise ultra-high data rates. However, efficient beam management remains challen

agentsarxiv-cs-ai

Neuron merging via inverse-activation regression for post-training compression of sigmoid neural networks

arXiv:2610.02559v1 Announce Type: new Abstract: As neural networks continue to grow in scale, model compression is becoming increasingly important for efficient inference under limited computational r

On-Board Anomaly Detection for Efficient Marine Environmental Monitoring

arXiv:2610.03649v1 Announce Type: cross Abstract: Marine ecosystems are impacted by various threats such as oil spills, algal blooms, and sediment floods, which disrupt habitats, wildlife, and human a

local-aiarxiv-cs-ai

Optimal Planning in a Dynamic World

arXiv:2610.03312v1 Announce Type: new Abstract: Background: We address the problem of planning when the set of feasible states or actions changes over time. For example, in the problem of path plannin

agentsarxiv-cs-ai

PoCoFL: POlicy-COmpliant Federated Learning

arXiv:2610.03650v1 Announce Type: cross Abstract: Federated Learning (FL) is a privacy-oriented learning paradigm that enables collaborative model training while keeping training data local to partici

safetyarxiv-cs-lg

Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning

arXiv:2610.02615v1 Announce Type: new Abstract: Learning research, as one of its central goals, tries to measure, model, and understand how learning-problem properties affect average-case learning per

Real-time Event-camera Stereo Visual Odometry via Keytime Gaussian Process Regression

arXiv:2610.02601v1 Announce Type: new Abstract: Event cameras have microsecond-level temporal resolution and high dynamic range which make them more resilient to motion blur and poor illumination than

researcharxiv-cs-ro

Relevant Evidence Decoding for Audio-Visual Hallucination Mitigation

arXiv:2610.02976v1 Announce Type: new Abstract: Audio-Visual Large Language Models (AV-LLMs) remain prone to cross-modal hallucinations, where one modality incorrectly affects predictions about anothe

Reward Inflation: A Healthy Stimulus for Reinforcement Learning

arXiv:2610.02545v1 Announce Type: new Abstract: Reward serves as the primary learning signal in reinforcement learning (RL). However, while reward magnitudes are typically held fixed throughout traini

safetyarxiv-cs-lg

RxnOptBench: Benchmarking LLMs for Reaction-Condition Optimization in Organic Methodology

model-releasesarxiv-cs-ai

arXiv:2610.02242v1 Announce Type: cross Abstract: Chemical reaction-condition optimization -- choosing the catalyst, ligand, solvent, reagent, temperature, time, and atmosphere that jointly maximize y

Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds

model-releasesarxiv-cs-lg

arXiv:2610.03165v1 Announce Type: new Abstract: Several variance-reduced versions of REINFORCE based on importance sampling achieve an improved O(epsilon^{-3}) sample complexity to find an epsilon-sta

Shrome at Touche: Soft-Vote Ensembling and Counter-Causal Augmentation for Causality Extraction

arXiv:2610.03268v1 Announce Type: new Abstract: Touche 2026 extends causality extraction to counter-causal claims: news sentences whose surface form appears causal but whose meaning denies the causati

researcharxiv-cs-cl

SideKernel: A Usable microVM Sandbox for AI Coding Agents on macOS

arXiv:2610.02456v1 Announce Type: cross Abstract: AI coding agents are untrusted system components, yet they require autonomy on the developer machines they run on. This contradiction is a security pr

local-aiarxiv-cs-ai

Smart Sensing for Safer Bridges: From Sensor Signals to AI-Driven Anomaly Detection

arXiv:2610.03082v1 Announce Type: new Abstract: Bridges contribute significantly to transportation connectivity and urban development. Therefore, reliable bridge monitoring is crucial for protecting p

safetyarxiv-cs-lg