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Artifact Annotations Partially Substitute for Per-User Calibration: SAFE-EDA and a Normalization-Controlled Evaluation of Wrist-EDA Affect Recognition

arXiv:2610.01692v1 Announce Type: new Abstract: Wrist electrodermal activity (EDA) differs in amplitude from one person to the next, so affect-recognition models normalize their input before classific

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Human DGX agent

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Research

Ask a Language Model for Lottery Numbers: Concentration in Repeated Six-of-49 Outputs

DGX agent

arXiv:2610.00052v1 Announce Type: cross Abstract: We evaluate six language-model configurations on requests for six distinct random integers from 1-49. Across 1,200 attempted calls using four English

researcharxiv-cs-ai

2 Oct 2026

AstroAgentBench: Evaluating Agentic Planning on Space Mission Planning Tasks

arXiv:2601.11354v2 Announce Type: replace Abstract: Recent LLM-for-Space systems address mission planning, scheduling, operations support, simulator control, and autonomy, but their evaluations use di

Asynchronous LLM Post-Training: Group-Mass Capping and Convergence Analysis

arXiv:2610.01896v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earl

ATI-VLA: Action-Centric Predictive Vision-Language-Action Models via Actionable Alignment Then Adaptive Injection

arXiv:2610.01741v1 Announce Type: new Abstract: Predictive Vision-Language-Action (VLA) models aim to improve robotic manipulation via future observation or world dynamics forecasting. However, existi

safetyarxiv-cs-cv

Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering

arXiv:2610.02014v1 Announce Type: new Abstract: The rapid maturation of artificial intelligence (AI) and machine learning (ML) has catalyzed a profound shift in how chemical engineering problems are f

agentsarxiv-cs-ai

Attention Kernels for Learning Maps Between Heavy-Tailed Measures

arXiv:2610.00564v1 Announce Type: new Abstract: Operator learning on probability measures can be accomplished with transformers. For measures with polynomial tails, the exponential weighting in softma

Attention Manifolds: Steering or Blocking Language Models by Editing Learned B-Spline Surfaces

arXiv:2610.00257v1 Announce Type: new Abstract: In standard transformer attention, a source token sends the same value vector to every receiver. The query determines how much to attend but not what to

Auditable Algebraic Counting Field for Cryptic-Pocket Detection from Apo Structures

arXiv:2610.00988v1 Announce Type: new Abstract: Cryptic ligand-binding pockets are not apparent in experimentally determined apo structures, making them difficult to identify from unbound receptor geo

Auditing Action Settlement in LLM Agent Environments: Order, Progress, and Replay

arXiv:2610.01138v1 Announce Type: new Abstract: Concurrent actions in large language model (LLM) agent environments require arbitration even when each proposal is individually valid. We implement a ty

Auditing Routing Entropy as an Uncertainty Signal in Attention-Residual Transformers

arXiv:2610.01495v1 Announce Type: new Abstract: Dynamic architectures leave a per-example routing trace beside each prediction, and diffuse routing is easy to read as a sign that the prediction is unr

AURAL: Adaptive Latent Reasoning with Joint Chunk for Speech Language Models

arXiv:2610.01560v1 Announce Type: cross Abstract: Model intelligence and fast response jointly shape the quality of interaction with speech language models, yet remain difficult to achieve together. E

Authorization for Self-Modifying AI Agent Populations: Conserving Authority across Replacement, Forking, and Rollback

arXiv:2610.00347v1 Announce Type: cross Abstract: Self-modifying AI agents can replace, fork, and roll back identity-bearing software while descendants remain executable. Per-successor authorization d

agentsarxiv-cs-ai

Auto-Formalizing Neuro-Symbolic Predictors

arXiv:2610.01519v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified c

AutoGUIWorld: Image Generators as Visual World Models for GUI Agent

arXiv:2610.01215v1 Announce Type: new Abstract: GUI agents require high-quality interaction trajectories to learn how software environments respond to actions, maintain state, and support multi-step w

agentsarxiv-cs-cv

Autoregressive Drillhole Modelling Under Distribution Shift

arXiv:2610.01204v1 Announce Type: new Abstract: Autoregressive modelling has achieved remarkable success in language and sequence tasks by learning to predict future states from previous observation.

AVSD-Scenes: A Dataset for Audio-Visual Description of Urban Scenes

arXiv:2610.01861v1 Announce Type: new Abstract: Natural language descriptions can provide rich semantic representations of audio-visual urban scenes, yet datasets that jointly describe both auditory a

Tutorials

Backdoor Containment via Expert Quarantine and Shutdown in LLMs

arXiv:2610.00663v1 Announce Type: new Abstract: Backdoored large language models (LLMs) can behave normally on benign inputs while producing attacker-specified outputs under hidden triggers. Existing

tutorialsarxiv-cs-ai

Backdoor Purification for LoRA-Tuned LLMs via Null-Space Projection

arXiv:2610.00685v1 Announce Type: new Abstract: With the rapid adoption of large language models (LLMs) and parameter-efficient fine-tuning (PEFT) methods, the risk of backdoor attacks has become more

BalLOT: Balanced k-means clustering with optimal transport

arXiv:2512.05926v2 Announce Type: replace-cross Abstract: We consider the fundamental problem of balanced k-means clustering. In particular, we introduce an optimal transport approach to alternating m

Before Agents Decide: Epistemic Action in LLM-Based Systems

arXiv:2610.00511v1 Announce Type: new Abstract: Before a difficult decision, people often act simply to understand the situation better. We turn an object to see another side, place alternatives next

agentsarxiv-cs-ai

Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs

arXiv:2610.01595v1 Announce Type: cross Abstract: Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet tempo

Bellman-Certified Rounding for Sparse Policy Deployment in MDPs

arXiv:2610.00325v1 Announce Type: new Abstract: Continuous policy optimization may spread an update across many states, even when deployment permits only a few complete state-level changes. We study h

safetyarxiv-cs-lg

Bellman Meets Lyapunov: Unsupervised Reinforcement Learning via Mastering Chaos

arXiv:2610.02012v1 Announce Type: new Abstract: Reinforcement learning (RL) is a powerful paradigm for training agents, yet its success rests on domain expertise of human engineers who design informat

agentsarxiv-cs-lg

Benchmarking Generative Models for Weather Data Assimilation on Real Station Observations

arXiv:2610.00728v1 Announce Type: cross Abstract: Weather reanalysis products rely on computationally intensive numerical weather predictions followed by data assimilation that corrects the forecast t

Benchmarking Prompt Optimization of Large Language Models With Chess

arXiv:2610.00416v1 Announce Type: new Abstract: Evaluating large language models becomes increasingly challenging as their capabilities advance: benchmarks can saturate, public test sets risk contamin

Benchmarking System One decision models against trained classifiers and language models for automated decision gates

arXiv:2610.00346v1 Announce Type: new Abstract: Software that hands branching decisions to a model needs a declared option and a probability it can threshold. Typed decision models, also called System

Better Convergence Guarantees for Sign-Based Momentum Methods

arXiv:2507.12091v2 Announce Type: replace-cross Abstract: This paper presents an improved analysis for sign-based methods with momentum updates. Traditional sign-based methods obtain a convergence rat

Beyond Affine Transformations: A Soft Dominance Layer for Coordinate-Wise Neural Computation

arXiv:2610.00563v1 Announce Type: cross Abstract: This paper presents a preliminary study of an alternative to the affine transformation underlying conventional neural-network layers. In the proposed

Beyond Answer Confidence: A Controlled Audit of Self-Knowledge in a Black-Box Decision Model

arXiv:2610.01006v1 Announce Type: new Abstract: Decision models return probabilities intended for routing, abstention and automated action. Calibration makes those probabilities useful on average, but

Beyond Decodability: Do Acoustic Factors Drive Predictions in Speech-Based Alzheimer's Assessment?

arXiv:2610.01846v1 Announce Type: cross Abstract: Speech-based Alzheimer's disease (AD) assessments increasingly rely on pretrained self-supervised learning (SSL) models that learn acoustic representa

safetyarxiv-cs-lg

Beyond Demographic Balance: Multi-Metric and Intersectional Evaluation of Fairness in MIMIC-IV Mortality Prediction

arXiv:2610.01645v1 Announce Type: new Abstract: Fairness conclusions in clinical prediction can depend strongly on both the metrics reported and the demographic resolution at which performance is eval

safetyarxiv-cs-lg

Beyond Diagonal State Space Models: Exact Non-Abelian Group Tracking, Solvability Barriers, and Geometric Physical Manifolds

arXiv:2610.00329v1 Announce Type: new Abstract: Selective state space models (SSMs), such as Mamba, S4D, and LRU, are bounded by transition matrix commutativity (A_t A_t' = A_t' A_t) and solvable affi

Beyond Domain-Level Adaptation: Margin-Oriented Semantic-Appearance Interaction Correction for Personalized Federated Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.01625v1 Announce Type: new Abstract: Federated parameter-efficient fine-tuning enables distributed clients to adapt pretrained vision-language models without sharing raw data or updating th

Beyond Final Accuracy: Auditing Communication in LLM Multi-Agent Systems

arXiv:2610.01042v1 Announce Type: new Abstract: Multi-agent communication aims to help agents benefit from one another's information. Yet improvements in system performance leave a fundamental ambigui

Beyond Leaderboard Scores: A Deployment-Focused Protocol for Interpretable Tracking Evaluation in Pedestrian-Centric Environments

model-releasesarxiv-cs-cv

arXiv:2610.01682v1 Announce Type: cross Abstract: Mobile robots operating among pedestrians need trajectories that become available quickly, remain spatially credible through missed observations, pres

Beyond Linear Concepts: Discovering and Aligning Non-Linear Concept Manifolds in Large Language Models

arXiv:2610.01821v1 Announce Type: new Abstract: Understanding information processing in large language models (LLMs) requires dissecting the geometric organization of their internal token representati

Beyond Memory: Harnessing Long-Horizon Agents with Explicit Belief States

arXiv:2610.01415v1 Announce Type: new Abstract: Large language model (LLM) agents can now undertake increasingly complex tasks, but the way they organize interaction history into memory does not ensur

Beyond Pixel Reconstruction: Retrieval-Guided Glyph-Aware Restoration for Low-Resource Manchu Historical Documents

arXiv:2610.00315v1 Announce Type: cross Abstract: Historical Manchu documents preserve invaluable linguistic and cultural heritage, yet their digitization is hindered by severe degradations and the sc

Beyond Pointwise Error: A Multi-Metric Evaluation of Spatial Climate Downscaling

arXiv:2610.01579v1 Announce Type: cross Abstract: Climate downscaling aims to reconstruct fine scale spatial fields from coarse resolution inputs. Evaluating the quality of these reconstructions is ch

Beyond State-of-the-Art: Standardising Environmental Impact Metrics for AI Research

arXiv:2610.01116v1 Announce Type: new Abstract: As the capabilities and ubiquity of Large Language Models (LLMs) grow, so does their environmental footprint. Despite calls for responsible AI, the mach

Beyond Supra-Competitive Outcomes: Collusive Behaviour in Deep Reinforcement Learning for Optimal Execution Games

arXiv:2610.00619v1 Announce Type: cross Abstract: In this paper, we extend earlier findings of supra-competitive outcomes in optimal-execution games by identifying a learned punitive mechanism that de

Beyond Unimodal Bases: Pullback Geometry for Multimodal Data

arXiv:2610.00708v1 Announce Type: new Abstract: Data-driven Riemannian geometry provides nonlinear interpolation and geometric representations of high-dimensional data. For these operations to be stat

BG4Sea: Biogeochemical Seasonal Forecastability via Progressive Information Scaling

arXiv:2607.16731v2 Announce Type: replace Abstract: Marine biogeochemical forecasting is increasingly important for managing marine ecosystems and the carbon cycle, yet global, seasonal forecast produ

Block Optimism for Nonstationary Bandits with Latent Linear Dynamics

arXiv:2610.00911v1 Announce Type: cross Abstract: We study an endogenous nonstationary stochastic bandit problem with latent linear dynamics, where actions affect both immediate rewards and the future

Applications

BLT*: Informed Belief Localization Trees for Uncertainty-Aware Planning on Digital Twins

arXiv:2610.01972v1 Announce Type: new Abstract: We present Informed Belief Localization Trees* (Informed BLT*), a sampling-based belief space planning (BSP) algorithm that scales to large outdoor digi

applicationsarxiv-cs-ro

Bootstrapping Video Interaction Generation with Synthetic State Transitions

arXiv:2610.01039v1 Announce Type: new Abstract: While recent video generative models can synthesize high-fidelity videos, they struggle to portray plausible physical interactions and the resulting sta

researcharxiv-cs-cv

Bounded-Fidelity Sim-as-Demo-Stage: Mocap Handoff for Governance Benchmarks

arXiv:2610.00008v1 Announce Type: cross Abstract: Sim-to-real research pursues physics fidelity as a primary objective: simulators are judged by how closely they reproduce real-world contact dynamics.