Search: “papers”

GateSight: Recurrent Memory Anticipates Attention Memory for Query-Agnostic KV Eviction in Hybrid LLMs

arXiv:2610.14754v1 Announce Type: new Abstract: Hybrid language models interleave Gated DeltaNet (GDN) layers, whose recurrent memory has a fixed size, with full-attention layers, whose key-value (KV)

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Geospatial Vector Geometry as a Native Spatial Modality for Vision-Language Models

DGX agent

arXiv:2610.16769v1 Announce Type: new Abstract: Geospatial reasoning links VLMs to real-world action and decision making. Reliable reasoning requires accurate spatial information and effective spatial

applicationsarxiv-cs-ai

15 Oct 2026

Get In, Decide, Prove: A Merchant-Side Readiness Benchmark for Agentic Commerce

arXiv:2610.17378v1 Announce Type: new Abstract: AI agents now browse and buy on people's behalf, and benchmarks measure how well the agents perform. Far less is known about the other side of the trans

HGRP: Heterogeneous Graph Neural Network for Routability Prediction

arXiv:2610.20209v1 Announce Type: new Abstract: Routability prediction enables rapid evaluation of placement quality without routing, providing effective feedback for routability-driven placement opti

researcharxiv-cs-lg

Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance

arXiv:2610.20607v1 Announce Type: cross Abstract: Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-d

High-Probability Regret Bounds for Feel-Good Thompson Sampling

arXiv:2610.19513v1 Announce Type: cross Abstract: Feel-good Thompson sampling (FGTS) augments the posterior of vanilla Thompson sampling with an exploration term that favors reward functions with high

researcharxiv-cs-lg

Tutorials

Hybrid supervised instance segmentation by learning label noise suppression

arXiv:2610.20412v1 Announce Type: new Abstract: To reach top accuracy, current fully supervised instance segmentation methods severely rely on large-scale pixel-wise labeled datasets. They are usually

tutorialsarxiv-cs-cv

Agents

HyperLoop: Hyperspectral-Assisted Loop Closure Detection in 3D-SLAM for Planetary Exploration

arXiv:2610.19742v1 Announce Type: new Abstract: Autonomous navigation of planetary rovers is challenged by visually repetitive, featureless terrain. SLAM systems based on 3D Gaussian Splatting (3DGS)

agentsarxiv-cs-cv

Identification of Entailment and Contradiction Relations for Natural Language Argumentation: A Neurosymbolic Approach

arXiv:2405.01259v2 Announce Type: replace Abstract: Argumentation is an important cognitive activity that involves the scrutiny of arguments and counterarguments. When given an argument, it is desirab

Infant Fingerprints: Quality Assessment & Recognition

model-releasesarxiv-cs-cv

arXiv:2610.20432v1 Announce Type: new Abstract: Infant fingerprint recognition is hindered by a combination of physiological characteristics, such as small ridge width and spacing, and acquisition cha

Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes

model-releasesarxiv-cs-cv

arXiv:2610.20585v1 Announce Type: cross Abstract: Current approaches for steady partial differential equations surrogate models on unstructured meshes apply a single mixing mechanism to the whole solu

Learning to Play: Reinforcement Learning and Games

arXiv:2610.17391v1 Announce Type: new Abstract: Amazing breakthroughs in reinforcement learning have taken place. Computers teach themselves to play Chess and Go and beat world champions. There is tal

Learning to Select Features with Manifold Deep Unfolding PCA

model-releasesarxiv-cs-cv

arXiv:2610.19436v1 Announce Type: new Abstract: Unsupervised feature selection (UFS) is of great significance in image processing and pattern recognition. Nevertheless, existing model-based methods of

LLM Alignment--Utility Asymmetry under Semantic-Preserving Transformations

arXiv:2609.32717v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) alignment is intended to ensure that models remain helpful and safe, but its stability under input distributional s

MasalBench: A Benchmark for Contextual and Cross-Cultural Understanding of Persian Proverbs in LLMs

model-releasesarxiv-cs-cl

arXiv:2601.22050v2 Announce Type: replace Abstract: In recent years, multilingual Large Language Models (LLMs) have become an inseparable part of daily life, making it crucial for them to master the r

Maximum-Entropy Exploration with Future State-Action Visitation Measures

arXiv:2603.18965v2 Announce Type: replace Abstract: Maximum entropy reinforcement learning motivates agents to explore states and actions to maximize the entropy of some distribution, typically by pro

Mechanistic Knobs in LLMs: Retrieving and Steering High-Order Semantic Features via Sparse Autoencoders

arXiv:2601.02978v3 Announce Type: replace-cross Abstract: Recent work in Mechanistic Interpretability (MI) has enabled the identification and intervention of internal features in Large Language Models

applicationsarxiv-cs-ai

Multi-Horizon Explainable Queue Forecasting and Resource-Aware Decision Support for Intelligent Border Control Using LightGBM

arXiv:2610.15930v1 Announce Type: new Abstract: Border crossing points are stochastic service systems in which traffic demand, traveler categories, registration status, inspection requirements, staffi

Narrative Paradoxes in LLM Inference: Shaping Reasoning Trajectories toward Misalignment

arXiv:2610.16312v1 Announce Type: new Abstract: Explicit reasoning in large language models (LLMs) is often associated with reliability, yet it can still pose risks when a model infers harmful goals u

NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning

arXiv:2603.06977v3 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) is increasingly used to design learning-enabled agents that interact in shared environments. However, trai

Neural POS Tagging for the Low-Resource Saraiki

model-releasesarxiv-cs-cl

arXiv:2610.20279v1 Announce Type: new Abstract: Part-of-speech tagging is a fundamental sequence labeling task and an important component for many downstream natural language processing applications.

Nudge the Judge: Uncovering Program Decision Hijacking in Real-World Jev Applications

arXiv:2610.18612v1 Announce Type: cross Abstract: System One models such as Jev change how software makes decisions by mapping open-ended semantic contexts into structured judgments that directly driv

applicationsarxiv-cs-ai

Pack Light, CarryOn: Building Object-Oriented Context for Long-Horizon Agents

arXiv:2610.18784v2 Announce Type: new Abstract: Long-horizon agents accumulate progress in persistent task state, yet repeatedly process interaction histories describing how that progress was achieved

PEAM: On-device Communication Agent for Personalized, Efficient and Autonomous Mobile Network Configuration

arXiv:2610.14855v1 Announce Type: new Abstract: The growing deployment of compact large language models on smartphones is enabling autonomous on-device decision-making, such as emerging mobile GUI age

Agents

Price of Anarchy of First-Price Auctions in Agentic Markets

arXiv:2610.20587v1 Announce Type: cross Abstract: An agentic market is a decentralized serving-time market where AI agents bid to claim each user prompt. An agent's bid is based on its expected value

agentsarxiv-cs-lg

Quantifying the Impact of Motion on 2D Gaze Estimation in Real-World Mobile Interactions

arXiv:2502.10570v3 Announce Type: replace-cross Abstract: Mobile gaze tracking on handheld devices commonly relies on appearance-based 2D gaze estimation from the device's front-facing RGB camera. Alt

applicationsarxiv-cs-cv

Reinforcement Learning via Advantage Guidance

arXiv:2610.19783v1 Announce Type: new Abstract: Reinforcement learning (RL) holds the promise of learning a policy that can outperform what is shown in the data. However, in practice, such systems suf

Relational Semantic Grounding for Test-Time Discovery

arXiv:2610.14721v1 Announce Type: new Abstract: Test-Time Discovery (TTD) aims to recognize known classes and detect novel ones from a continuous unlabeled test stream after deployment. Existing TTD m

safetyarxiv-cs-ai

Reliable Text-to-SQL in Resource-Constrained Settings with Small LLMs via Iterative Retry Workflows

arXiv:2610.17305v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently improved Text-to-SQL generation, but their computational cost can hinder deployment in resource-constrained s

RetailAgent: Structured Adverse Timing in Self-Conditioned Multimodal LLM Trading Agents

arXiv:2608.28399v2 Announce Type: replace Abstract: In financial markets, a sequential policy that reacts systematically to price movements may become predictable to other market participants. This pa

safetyarxiv-cs-ai

Retrieval Over Training: Similarity search-based Model Selection for Time Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2610.20243v1 Announce Type: new Abstract: Anomaly detection is a fundamental task for time-series analytics, with important implications for the downstream performance of many applications. Desp

RoboSpan: Learning Modular Coordination Policies for High-DoF Whole-Body Mobile Manipulation with Teleoperation

arXiv:2610.19594v1 Announce Type: new Abstract: Whole-body mobile manipulation suffers from two fundamental challenges: inherent motion heterogeneity across locomotion, arm, and hand modules, and prog

researcharxiv-cs-ro

Robust Real-Time Monocular Human Pose Estimation with Insole-Based Sensor Fusion

arXiv:2610.19494v1 Announce Type: new Abstract: Real-time monocular human pose estimation is an important sensing component for human-centered intelligent systems. While recent camera-based methods ha

researcharxiv-cs-cv

Same Attack, Different Judge: A First Controlled Adversarial Comparison of Jev, LLM Judges, and Purpose-Built Safety Classifiers

arXiv:2610.17820v1 Announce Type: cross Abstract: TypeSafe AI's Jev is a new kind of safety judge. It generates no text and no label: it answers questions the developer defines in advance and returns

SaTPO: Text-to-Image Safety Alignment via Transition Preference Optimization

arXiv:2610.19563v1 Announce Type: new Abstract: Safety alignment of text-to-image diffusion models aims to suppress harmful content without compromising useful generation capabilities. However, prefer

safetyarxiv-cs-cv

Agents

Scaling Discovery Requires Forgetting

arXiv:2610.20563v1 Announce Type: cross Abstract: Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are c

agentsarxiv-cs-cl

Hardware

Scaling LLM Inference via Parallelism: Throughput-Latency Trade-off

arXiv:2610.19405v1 Announce Type: cross Abstract: Large Language Model (LLM) serving systems must balance latency and throughput while efficiently utilizing distributed GPU resources. This challenge a

hardwarearxiv-cs-lg

SchemaWeaver: Accelerating On-Device Mobile Agentic AI via Schema-Guided Parallel LLM Decoding

arXiv:2610.17436v1 Announce Type: new Abstract: Large language models (LLMs) on mobile devices can act as agents that call external software tools to complete complex tasks, but the major challenge of

Tutorials

Score-Based Training for Energy-Based TTS Models

arXiv:2505.13771v2 Announce Type: replace-cross Abstract: Noise contrastive estimation (NCE) is a popular method for training energy-based models (EBM) with intractable normalisation terms. The key id

tutorialsarxiv-cs-lg

Seamless Deployment of Machine Learning Inference at the Far Edge: An Empirical AWS IoT Greengrass Architecture for Industrial Predictive Maintenance

arXiv:2610.14815v1 Announce Type: cross Abstract: Industrial IoT sensors produce continuous, high-volume data streams that predictive maintenance needs to analyse in real time. Cloud-centric architect

Selective Prediction Forgetting for Adaptation of Weakly Supervised Localization of Histology Images

arXiv:2603.12468v2 Announce Type: replace Abstract: Under strong cross-domain shifts, weakly supervised object localization (WSOL) models often lose their capacity to discriminate and develop a strong

local-aiarxiv-cs-cv

Similar Models, Broken Odds: Where Luce's Axiom Fails in Chatbot Arena

arXiv:2610.19095v1 Announce Type: new Abstract: Chatbot Arena ranks language models with the Bradley-Terry model, which gives each model one score and so assumes Luce's choice axiom. Choice theory pre

researcharxiv-cs-cl

SoK: Grading Open-Text Legal Answers, from Law School Exams to Trustworthy Rubric Judges

arXiv:2610.19992v1 Announce Type: new Abstract: Law students are examined through open-text answers: case solutions, essays and memos that apply the law to a set of facts. Such answers are expensive t

applicationsarxiv-cs-cl

SPARS: A Stability-Plasticity-Aware Region Selection Framework for Continual Learning

model-releasesarxiv-cs-lg

arXiv:2610.19876v1 Announce Type: new Abstract: Continual learning aims to acquire new knowledge while retaining previously learned knowledge. However, updating shared parameters when learning new tas

Specification-Guided Synthesis of Deadlock-Free Communication Protocol Refinements with Large Language Models

arXiv:2607.27964v3 Announce Type: replace-cross Abstract: Ensuring behavioural correctness in communication protocols is a central challenge in distributed software systems, as subtle inconsistencies

StableJudge: A Lightweight Adversarial Defense Framework for LLM-as-a-Judge

arXiv:2610.16814v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as judges to assign scalar scores that drive downstream decision-making, including tasks such as pa

Stochastic CHAOS: Why Deterministic Inference Kills, and Distributional Variability Is the Heartbeat of Artifical Cognition

arXiv:2601.07239v2 Announce Type: replace Abstract: Deterministic inference is a comforting ideal in classical software: the same program on the same input should always produce the same output. As la

safetyarxiv-cs-ai

Structure-Preserving Document-Level Data Augmentation via Discourse Parsing

arXiv:2610.19497v1 Announce Type: new Abstract: Data augmentation (DA) plays a vital role in improving model performance in low-resource or limited-supervision scenarios within Natural Language Proces

researcharxiv-cs-cl