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Evaluating Local Language Model Agents for Reproducible Data Engineering: An Empirical Software Engineering Study of Mobility Workflows

arXiv:2610.11482v1 Announce Type: cross Abstract: Context: Large language model (LLM) agents are increasingly used as software and data-engineering assistants, yet evidence about locally deployable op

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Model Releases

Evaluating Rubric Generation with Interventional Transfer

DGX agent

arXiv:2610.10809v1 Announce Type: new Abstract: Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale,

model-releasesarxiv-cs-lg

9 Oct 2026

Event-Centric Memory with Query-Aware Graph Augmentation for Long-Term Conversational Agents

arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing pas

local-aiarxiv-cs-cl

Tutorials

Evi-VN: Hard Region Guided Virtual Node Evidence Injection for GNN-Based Fraud Detection

arXiv:2610.11665v1 Announce Type: new Abstract: Online platforms contain growing numbers of bots, deceptive reviewers, and scam accounts that imitate legitimate users. Such camouflage blurs graph neig

tutorialsarxiv-cs-lg

Evidence-Traceable Dynamic Interviewer Architecture for Expertise-Adaptive Qualitative Interviews Using Local LLMs

arXiv:2610.11651v1 Announce Type: new Abstract: Automated interviewers and conversational agents are increasingly used in research, recruitment, customer service, and education. However, many existing

local-aiarxiv-cs-ai

Agents

EvoAlloc: A Self-Evolving Resource Allocation Agent for Efficient Program Evolution

arXiv:2610.12086v1 Announce Type: new Abstract: LLM-based program evolution relies on evaluation feedback to guide the iterative search for high-performing programs. However, evaluation is often compu

agentsarxiv-cs-ai

EvoKnow: Continual Knowledge Evolution for AI-Generated Image Detection

arXiv:2610.11381v1 Announce Type: cross Abstract: AI-generated image detectors are commonly trained on fixed generator domains and become difficult to maintain as new generative models emerge. Continu

Agents

EvoSim: Learning to Model, Modeling to Learn

arXiv:2610.11344v1 Announce Type: new Abstract: Physics-based models connect scientific explanation with quantitative prediction. Constructing them requires selecting physical processes, defining stat

agentsarxiv-cs-ai

Exact SO(3)-Equivariant Isotropic Kernels for Rotation-Robust Neural Dynamics

model-releasesarxiv-cs-lg

arXiv:2610.10626v1 Announce Type: new Abstract: Neural surrogates for vector-valued partial differential equations can fit training data yet change their predictions when the same physical state is ex

Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology

arXiv:2610.12022v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external

Tutorials

Example-driven Parametrisations for Bayesian Shape Optimisation

arXiv:2610.11984v1 Announce Type: new Abstract: Bayesian optimisation is the natural tool for shape design when objectives are expensive and non-differentiable, but it needs a compact yet expressive p

tutorialsarxiv-cs-lg

ExecVLA: Following Fine-Grained Execution Constraints in Vision-Language-Action Models with Bi-Level Action Representation

arXiv:2603.17524v2 Announce Type: replace-cross Abstract: We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must fol

safetyarxiv-cs-ai

Applications

Experience-Guided Initiation Search for Learned Skills in Skill Composition

arXiv:2610.11418v1 Announce Type: new Abstract: Deploying frozen learned skills, such as Vision-Language-Action (VLA) policies, in new environments requires identifying initiation configurations that

applicationsarxiv-cs-ro

Explaining the Saliency Map Sparsity of Adversarially-Trained Neural Networks

arXiv:2610.10666v1 Announce Type: new Abstract: Understanding why deep neural networks make a given prediction is of great importance for their safe deployment. In computer vision, saliency maps, whic

researcharxiv-cs-lg

Explanation Multiplicity in SHAP: Characterization and Assessment

arXiv:2601.12654v3 Announce Type: replace-cross Abstract: SHAP explanations are widely used in high-stakes settings to justify decisions, yet they can differ substantially across repeated runs, even w

researcharxiv-cs-ai

Tutorials

Exploiting Gradients in Bayesian Inference of Expensive Simulators

arXiv:2610.12076v1 Announce Type: new Abstract: Simulators based on differential equations are ubiquitous in science and engineering. They are often used in simulation-based inference to evaluate the

tutorialsarxiv-cs-lg

Expression-Diverse References for Identity-Preserving Video Generation

arXiv:2610.11023v1 Announce Type: new Abstract: Identity-preserving video generation aims to maintain a subject's identity while synthesizing realistic videos. Yet a single reference portrait captures

F^3NO: Frequency-Decomposed Finite-Time Flow-map Neural Operators with Cross-Scale Conditioning

arXiv:2610.10998v1 Announce Type: new Abstract: Neural operators enable fast PDE forecasting, but repeated predictions accumulate errors and fine-scale structures remain difficult to resolve. We intro

local-aiarxiv-cs-lg

FA-Bench: A Benchmark for Phone- and Word-Level Timestamp Accuracy in Forced Alignment and ASR on Clean and Noisy Speech

arXiv:2609.32396v2 Announce Type: replace Abstract: Forced alignment estimates the timestamps of each word, phone or character in speech given its transcript. Published comparisons normalize transcrip

Fact over Fiction: Detection of Pathological Hallucinations in Sinhala-to-English Neural Machine Translation

arXiv:2610.11389v1 Announce Type: new Abstract: Neural Machine Translation (NMT) models, while capable of producing highly fluent outputs, remain vulnerable to hallucinations, which are translations t

FAITH: Feasibility-Aware Safety-Filtered RL for High-Dimensional Systems

arXiv:2610.12432v1 Announce Type: cross Abstract: Safe reinforcement learning commonly places safety and task performance in the same policy objective, where they can introduce competing updates. Safe

safetyarxiv-cs-lg

False Claims, Credible Images: A Red-Teaming Benchmark for Commercial Image Generators

arXiv:2610.11112v1 Announce Type: cross Abstract: Image-generation models can now produce text-rich, natural-looking visual artifacts that are hard to distinguish from real-world evidence, such as new

Fast Pose Tracking of Rigid Objects with Compact Pose Graph Optimization

arXiv:2610.11815v1 Announce Type: new Abstract: Tracking a novel object's 6D pose over long horizons currently requires either expensive onboarding or a reconstruction maintained throughout the sequen

safetyarxiv-cs-cv

FastBench: Can Streaming VLMs Perceive High-Dynamic Real-World Streams?

arXiv:2610.12427v1 Announce Type: cross Abstract: Streaming Video Large Language Models (VLMs) enable continuous video understanding, yet existing benchmarks focus on low-dynamic scenarios. Under boun

FastJEV: Understanding Redundancy for Compact JEV Inference

arXiv:2610.11379v1 Announce Type: new Abstract: JEV models make multimodal decisions by directly scoring candidates. Although the common context is encoded once, candidate evaluation can still repeat

researcharxiv-cs-cv

FearCaut-Qwen: Affective Steering in a Vision-Language Model Shifts the Decision Criterion for Hazard Assessment

arXiv:2610.11986v1 Announce Type: new Abstract: Vision-language models (VLMs) show great potential for damage assessment after a disaster, but a recurring deficiency is that they are reluctant to decl

Feature Space Adaptation for Effortless Gaussian Process Flows

arXiv:2610.11459v1 Announce Type: cross Abstract: Outside the linear-Gaussian regime, conditional sampling from Gaussian processes (GPs) is challenging. Recent methods such as FlowGP (Moss et al., (20

researcharxiv-cs-lg

Fed-GRPO: Reward-Signal-Driven Federated Group Relative Policy Optimization

arXiv:2610.11502v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong reasoning capabilities when fine-tuned with reinforcement learning (RL), particularly through Group Relat

local-aiarxiv-cs-ai

FedAlphaEdit: Null-Space-Aligned Merging for Collaborative Knowledge Editing

arXiv:2610.11033v1 Announce Type: new Abstract: Multiple institutions may each hold their own private knowledge edits and wish to integrate them into a single large language model without sharing raw

local-aiarxiv-cs-cl

Few-Step Generation via Data-Space Iteration

arXiv:2610.12102v1 Announce Type: cross Abstract: Flow matching has emerged as a scalable paradigm for training high-quality generative models, but sampling from the learned probability flow requires

researcharxiv-cs-cv

Finsler Flow Matching: Dynamics-Aware Geodesic Interpolation for Single-Snapshot Trajectory Inference

arXiv:2610.11318v1 Announce Type: new Abstract: Single-cell snapshot data can resolve a continuum of cellular states but do not uniquely determine the dynamics governing transitions between them. Howe

local-aiarxiv-cs-ai

Fixed-Reference Pose Residuals for Measuring Cross-Dataset Cue Transfer in Human-Robot Interaction Anticipation

arXiv:2610.12245v1 Announce Type: new Abstract: Social and service robots in public spaces need to anticipate which nearby person is about to approach and touch them, so that a response can be prepare

researcharxiv-cs-ro

FloorSAV: Elucidating Spatial Audio-Visual Context with 2D Floormap for AV-LLMs

arXiv:2610.11310v1 Announce Type: new Abstract: While 3D spatial reasoning in dynamic egocentric environments is crucial for embodied intelligence, audio-visual large language models (AV-LLMs) lack ex

FlowState: Execution State as Memory for Long-Horizon LLM Agents

arXiv:2609.34565v2 Announce Type: replace Abstract: Long-horizon tasks require LLM agents to continually draw on information from earlier interactions. However, retaining the full history increases co

Fluid-Gen-Zero: Grounding Pretrained Video Generators in Physics without Training

arXiv:2610.10984v1 Announce Type: new Abstract: We present Fluid-Gen-Zero, a training-free framework for physics-aware fluid-object interaction video generation that decouples physical reasoning from

FlyMark: Training-Free Invisible Watermarking of 3D Gaussian Splatting via a Fruit Fly Connectome

arXiv:2610.11364v1 Announce Type: new Abstract: A trained 3D Gaussian Splatting (3DGS) scene ships as a portable parameter array that can be copied, pruned, requantized, or repackaged outside its trai

FOCUS: From Privileged States to RGB-D with Controlled Modality Switching and Representation Alignment

arXiv:2610.11119v1 Announce Type: new Abstract: Vision-based reinforcement learning for robotic manipulation is sample-inefficient because RGB-D observations are high-dimensional and noisy. Privileged

safetyarxiv-cs-ro

Agents

Forms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System

arXiv:2610.11899v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly embedded as components in software systems, marketed under labels such as chatbot, copilot, retrieval-au

agentsarxiv-cs-ai

Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size

arXiv:2510.04440v2 Announce Type: replace Abstract: We develop a source-driven fractional heat-kernel framework for semi-super-vised graph learning that combines nonlocal propagation with sustained la

researcharxiv-cs-lg

Freeze the Decoder, Heal the Encoder: Parameter-Efficient Adaptation for SVD-Based KV-Cache Compression

arXiv:2610.10552v1 Announce Type: cross Abstract: Comparing parameter-efficient fine-tuning recipes under a single, shared learning rate is a common but flawed practice: when the arms being compared h

Fresco++: Frequency-Guided and Canonical-Consistent Optimization for Fine-Grained Head Avatar Modeling

arXiv:2610.11412v1 Announce Type: new Abstract: We propose Fresco++, a unified optimization framework for fine-grained and view-consistent head avatar reconstruction. Head avatar optimization is typic

researcharxiv-cs-cv

Fresh updates for dots. First up: you can now create your dot straight from your phone in the ChatGPT app on iOS and Android.

ChatGPT introduced a new mobile feature on October 9 2026 that lets users create dots directly within the ChatGPT app on iOS and Android devices. The update adds in‑phone dot creation, streamlining wo

model-releasesopenai--x

FreshMem: Brain-Inspired Frequency-Space Hybrid Memory for Streaming Video Understanding

arXiv:2602.01683v2 Announce Type: replace-cross Abstract: Transitioning Multimodal Large Language Models (MLLMs) from offline to online streaming video understanding is essential for continuous percep

researcharxiv-cs-ai

From a Prompt to Repertoires: Evolving Functional REpertoires Enable LLM Continual Learning

arXiv:2610.11373v1 Announce Type: cross Abstract: Continual learning remains challenging for large language models, which must enable models to acquire new skills and knowledge without degrading exist

From Chain-of-Thought to Loops: Non-Autoregressive Latent Reasoning via Looped Transformers

arXiv:2610.11472v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning often improves language-model performance by giving models additional computation before answering. However, explicit C

researcharxiv-cs-ai

From Geometry to Generalization: Why Row Normalization Can Beat Adam and Muon

arXiv:2610.11309v1 Announce Type: cross Abstract: Different optimizers can fit the same training data while selecting classifiers with substantially different geometries, but whether this difference p

safetyarxiv-cs-ai

From Investigation Failures to Reliable SOC Agents: Understanding and Improving LLM-Based Alert Triage

arXiv:2610.10608v1 Announce Type: cross Abstract: Security operations centers (SOCs) must triage large volumes of alerts, most of which are benign, while missed attacks can remain uninvestigated. Tool

From Language to Motion: Task-Conditioned Focal-Stack Trajectory Integration for Microscopic Robots

arXiv:2610.12241v1 Announce Type: new Abstract: Microscopic robots require accurate task geometry despite changes in language, parts, and focus. We present a semantic-to-physical framework that maps i

researcharxiv-cs-ro