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COFFEQA: Counterfactual-Guided Few-Shot Distillation for LLM Question Answering

arXiv:2610.12837v1 Announce Type: cross Abstract: Knowledge distillation aims to train a smaller student model to mimic a larger teacher model for resource-constrained environments. However, the proce

researcharxiv-cs-ai

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CoGameReg: Cooperative-Game-Based Collaborative Semi-Supervised Regression for Seismic Reservoir Property Prediction

DGX agent

arXiv:2610.12884v1 Announce Type: new Abstract: Accurate estimation of reservoir properties from seismic data remains challenging when well-log labels are sparse but three-dimensional seismic observat

model-releasesarxiv-cs-lg

12 Oct 2026

Collaborative Learning and Reasoning over Model Slices

arXiv:2610.12927v1 Announce Type: new Abstract: Large language models (LLMs) excel across diverse tasks, benefiting from knowledge priors, in-context reasoning, and test-time computation. Despite thes

Collaborative Theory of Mind: Learning to Self-Revise by Anticipating User Responses

arXiv:2610.12872v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong individual task performance, yet still struggle to collaborate with users over extended, multi-turn inte

safetyarxiv-cs-ai

Collective Autonomous Vehicle Routing Needs Social Awareness for Coexistence with Human Drivers

arXiv:2610.13439v1 Announce Type: cross Abstract: Collective Autonomous Vehicle (AV) route choices in real-world traffic networks can create externalities for Human-Driven Vehicles (HDVs), as routes t

agentsarxiv-cs-ai

Competence-Aware Orchestration for LLM-Based Multi-Agent Systems

arXiv:2610.13144v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have emerged as a promising paradigm for enhancing complex reasoning through role specialization and collaboration,

agentsarxiv-cs-ai

Constrained Probabilistic Numerics: Gaussian Process Solvers for Linear PDEs under Linear Inequality Constraints

arXiv:2610.13804v1 Announce Type: cross Abstract: Gaussian process solvers for linear partial differential equations (PDEs) return posteriors rather than point estimates, but they condition only on eq

Constructing Pareto Frontiers of Optimal Reasoning Termination Methods for Overthinking in Reasoning Models

arXiv:2610.13570v1 Announce Type: new Abstract: Reasoning models can benefit from test-time scaling, but continued reasoning may become ineffective or harmful, a phenomenon termed overthinking. Evalua

Contextual Correction of Parallel Draftsfor Speculative Decoding

arXiv:2610.12570v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference by using a lightweight drafter to propose multiple tokens that are subsequently verified

researcharxiv-cs-cl

Continually Post-training Small Models via Synthetic Self-distillation

arXiv:2610.13113v1 Announce Type: cross Abstract: Continual post-training faces a dual challenge of acquisition and retention: models must learn new capabilities while preserving prior knowledge. Whil

local-aiarxiv-cs-ai

Controlled-Minimax: Stabilizing Adversarial Optimization via Control Theory

arXiv:2610.12915v1 Announce Type: new Abstract: Minimax optimization is fundamental to adversarial learning yet suffers from severe stability challenges, often manifesting as persistent limit cycles o

Cooperative Aerial Transportation of a Payload with a Sliding Cable Attachment

arXiv:2610.13665v1 Announce Type: new Abstract: This paper presents a dual-quadrotor hook- suspended transport system for cooperative aerial manipulation of a payload that is not rigidly attached to a

researcharxiv-cs-ro

Coordinate-Free Automatic Differentiation

arXiv:2610.12776v1 Announce Type: new Abstract: Automatic differentiation (AD) is a cornerstone of modern machine learning. Since all AD frameworks implicitly fix a basis of Euclidean space to define

CopRoute: Dependence-Aware Conformal Routing for Language Models

arXiv:2610.13276v1 Announce Type: new Abstract: Set-based language model routing aims to increase the coverage of the event where at least one model answers a query correctly while controlling the num

safetyarxiv-cs-lg

CORAL-KV: Compact Cross-Layer Prediction and Residual Coding for Autoregressive Video KV Caches

arXiv:2610.12514v1 Announce Type: cross Abstract: Autoregressive video diffusion models maintain a growing attention key-value (KV) cache, making memory a key bottleneck for long video generation. Rec

local-aiarxiv-cs-lg

CORE-Seg: Reasoning-Driven Segmentation for Complex Lesions via Reinforcement Learning

arXiv:2603.05911v2 Announce Type: replace-cross Abstract: Medical image segmentation is undergoing a paradigm shift from conventional visual pattern matching to cognitive reasoning analysis. Although

Tutorials

CorrFlow: Exact and Permutation-Equivariant Flow Matching on the Correlation Elliptope

arXiv:2610.13606v1 Announce Type: cross Abstract: Correlation matrices combine nonlinear positive-definiteness constraints with a simultaneous row-column permutation symmetry. Their generation therefo

tutorialsarxiv-cs-lg

Credit Attribution in Timestamped Soccer Networks Using Multivariate Hawkes Processes

arXiv:2610.12775v1 Announce Type: cross Abstract: The two main traditional player statistics used in soccer are goals scored and assists, with an assist credited when a player's pass immediately leads

Critical Mass: Structure-Disjoint Splits Drift With the Libraries They Are Built On

arXiv:2610.12694v1 Announce Type: new Abstract: Molecular machine learning evaluates out-of-distribution performance with structure disjoint splits, a construction rule fixed once at the scale its lib

CRM: Retrieval Model with Controllable Condition

arXiv:2412.13844v2 Announce Type: replace-cross Abstract: Retrieval models for recommendation need to account for outcomes such as watch time while searching large item corpora efficiently. We present

researcharxiv-cs-ai

Cross-Behavior Policy Optimization: Unified Learning from Offline Demonstrations and On- and Off-Policy Rollouts via a Shared Regression Target

arXiv:2610.12830v1 Announce Type: new Abstract: Reasoning post-training draws on offline demonstrations and policy-generated rollouts, yet conventional supervised fine-tuning (SFT) followed by reinfor

Cubic Spline Interpolation for Smooth Trajectory Generation in Autonomous Motion Systems

arXiv:2610.12826v1 Announce Type: new Abstract: We presented a program that automates the construction and solution of the cubic spline interpolation problem for a sequence of position-time waypoints,

agentsarxiv-cs-ro

CV-OPD: Contrastive Vision On-policy Distillation

arXiv:2610.13264v1 Announce Type: cross Abstract: On-policy distillation (OPD) reveals versatility and convenience during VLM post-training, providing dense supervision for student from teacher. Howev

safetyarxiv-cs-lg

DAG Structure Learning with Node-Varying Heavy-Tailed Disturbances

arXiv:2610.13304v1 Announce Type: new Abstract: DAG structures can be learned from observations by incorporating acyclicity via smooth constraints, such as DAGMA's log-determinant function. Typically,

Data-Adaptive Mahalanobis Metric Learning for Cross-Head Attention in Transformers

arXiv:2610.13261v1 Announce Type: new Abstract: In this paper, we propose Data-Adaptive Mahalanobis Cross-Head Attention (DAMCHA), a simple and effective attention mechanism that generalizes Multi-Hea

Data-driven Optimal Sensor Placement for Aerosol Monitoring in the UK

arXiv:2610.12658v1 Announce Type: new Abstract: We develop a data-driven sensor-placement framework and apply it to aerosol monitoring in the United Kingdom (UK). A trained convolutional Gaussian neur

Data-Driven Stochastic Optimal Control in Reproducing Kernel Hilbert Spaces

arXiv:2407.16407v3 Announce Type: replace-cross Abstract: This paper proposes a fully data-driven approach for optimal control of nonlinear control-affine systems represented by a stochastic diffusion

agentsarxiv-cs-lg

DataCupid: Stable Matching Repair for Training Data Acquisition with Delayed Feedback

arXiv:2610.12960v1 Announce Type: new Abstract: Matching repair after utility changes can reuse valid observations, but new evaluations must respect matching capacity and may return out of order. We s

DEAF: A Benchmark for Diagnostic Evaluation of Acoustic Faithfulness in Audio Language Models

arXiv:2603.18048v3 Announce Type: replace Abstract: Recent Audio Multimodal Large Language Models (Audio MLLMs) demonstrate impressive performance on speech benchmarks, yet it remains unclear whether

Tutorials

Decoding Register Tokens Preserves Global Scene Details

arXiv:2610.13299v1 Announce Type: cross Abstract: Pretrained vision transformers learn structured image representations spanning spatial patch tokens and non-spatial tokens. Recent analyses suggest th

tutorialsarxiv-cs-lg

Deep End-to-End Survival Analysis with Temporal Consistency

arXiv:2410.06786v2 Announce Type: replace Abstract: In this study, we present a novel Survival Analysis algorithm designed to efficiently handle large-scale longitudinal data. Our approach draws inspi

Defence against the dark arts of distillation: Unsupervised discovery of subliminal learning

arXiv:2610.13536v1 Announce Type: cross Abstract: When a language model is distilled from a teacher that shares its base parameters, the student can inherit behavioural traits of the teacher---includi

DeFiRank: Federated Pairwise Ranking for Governance in Decentralized Financial Networks

arXiv:2610.12916v1 Announce Type: new Abstract: Existing governance approaches in decentralized financial networks rely on manual review processes conducted by human committees, which introduces subje

safetyarxiv-cs-ai

Applications

DeFM: Learning Foundation Representations from Depth for Robotics

arXiv:2601.18923v2 Announce Type: replace Abstract: Depth sensors are widely deployed across robotic platforms, and advances in fast, high-fidelity depth simulation have enabled robotic policies train

applicationsarxiv-cs-ro

DeltaLLM: Delta-Key Sparse Attention for Edge LLMs

arXiv:2507.19608v2 Announce Type: replace Abstract: On-device LLM inference is increasingly important for edge platforms but remains challenging due to high computational and memory demands and tight

local-aiarxiv-cs-ai

Deploying RDMA for Large-Scale Inference and Training Workloads

arXiv:2610.12815v1 Announce Type: new Abstract: RDMA can reduce communication overhead in distributed machine learning systems, but realizing these benefits in production requires more than replacing

Desertification Forecasting in Semi-Arid Regions: Using Deep Learning to Probe the Observability Limits of Land Degradation Dynamics

arXiv:2610.13406v1 Announce Type: cross Abstract: Forecasting desertification has received far less attention than mapping it. We use a convolutional LSTM (ConvLSTM) trained on ten annual Earth Observ

Designing Protein Structures from Natural Language

arXiv:2610.13917v1 Announce Type: new Abstract: A central challenge in de novo protein design is generating proteins with desired structural and functional properties. Existing design models typically

Development of a Low-Cost Prosthetic Hand Using Electromyography and Machine Learning

arXiv:2411.15533v2 Announce Type: replace Abstract: Electromyography (EMG) is a measure of muscular electrical activity and is used in many clinical/biomedical disciplines and modern human computer in

researcharxiv-cs-ro

DiffMorphGrasp: A Diffusion Framework Conditioned on Hand Morphology for Cross-Embodiment Grasp Generation

model-releasesarxiv-cs-ro

arXiv:2602.00915v2 Announce Type: replace Abstract: As robots are deployed across diverse environments, manipulation tasks require robot hands with different morphologies to satisfy varying task requi

Applications

Diffusion Precipitation Generation with Medium-range Weather Forecasting

arXiv:2610.12976v1 Announce Type: new Abstract: Accurate daily precipitation forecasts are important for weather-sensitive decisions. Although recent Weather Foundation Models (WFMs) have achieved sig

applicationsarxiv-cs-lg

DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models

arXiv:2610.12572v1 Announce Type: new Abstract: Online reinforcement learning (RL) fine-tunes diffusion models with black-box rewards, but reverse-process methods such as Flow-GRPO are limited in effi

safetyarxiv-cs-lg

Applications

Discovering Phase Space Structure in Learned Hamiltonian Systems

arXiv:2509.23003v3 Announce Type: replace-cross Abstract: Mechanics-inspired neural dynamical models improve interpretability and physical consistency, but they usually assume a known configuration sp

applicationsarxiv-cs-ai

Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models

arXiv:2502.08598v3 Announce Type: replace Abstract: Diffusion models have been widely adopted as a powerful generative framework across numerous scientific domains, yet their inherently iterative samp

DistressBench: Evaluating Multi-Dimensional Crisis Support in Large Language Models

arXiv:2610.12758v1 Announce Type: new Abstract: Language models have been adopted faster than evaluation practices that reliably assess their risks, and a growing share of use is affective rather than

safetyarxiv-cs-cl

Distributed Harmonic-Covariance Feedback for Hole Closure in Planar Robot Swarms

arXiv:2610.12637v1 Announce Type: new Abstract: We consider hole closure in a planar multi-agent system whose sensing disks form a time-varying Cech complex. We propose a harmonic-covariance feedback

local-aiarxiv-cs-ro

Distributionally Robust Adaptive Iterative Covariance Steering for Small-Body Proximity Operations

arXiv:2610.12774v1 Announce Type: cross Abstract: Autonomous small-body proximity operations require continuous-thrust guidance under uncertain gravity, solar-radiation pressure (SRP), and stochastic

safetyarxiv-cs-ro

Diversity-Aware Ensemble of Quantum-Classical Models via Combinatorial Fusion

arXiv:2610.13808v1 Announce Type: cross Abstract: Variational quantum circuits (VQCs) are highly sensitive to circuit architecture, yet most quantum machine learning pipelines select a single best des