Search: “model-releases”

When Pleasing the User Compromises Care: AI Sycophancy in Caregiver-Mediated Healthcare

arXiv:2610.14360v1 Announce Type: new Abstract: Large language model (LLM) alignment often assumes that the user interacting with a model is also the primary beneficiary of its behavior. Yet in many c

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Model Releases

When Should Enterprise Policy Decisions Be Learned, and When Should They Be Reasoned?

DGX agent

arXiv:2610.17643v1 Announce Type: new Abstract: An enterprise agent that answers under a written policy must choose an action before it says anything: answer, ask for a missing fact, ask for confirmat

model-releasesarxiv-cs-ai

15 Oct 2026

When Skills Remain But Access Fails: Factorized Skill Memory for Continual Skill Internalization

arXiv:2610.15492v1 Announce Type: new Abstract: Skill internalization aims to convert externally specified procedural skills into persistent model capabilities, allowing language-model agents to execu

Where Should the Gaussians Go? Reusable Label-Aware Allocation for Budget-Constrained Gaussian Splatting of Cinematic CT

arXiv:2610.20397v1 Announce Type: new Abstract: Anatomical labels help 3D Gaussian splatting preserve vessels in cinematic renderings of CT, but the representation is still found by optimising each pa

Which Metadata Matters for LLM Tool Selection in MCP? Evidence from Controlled Factor-Level Interventions

arXiv:2610.14334v1 Announce Type: new Abstract: In Model Context Protocol (MCP) systems, LLMs select tools from metadata rather than from their implementations. Names and descriptions summarize what a

Who's Behind the Text? Robust Model Authorship Attribution

model-releasesarxiv-cs-cl

arXiv:2610.19583v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly used to generate text, their misuse has become a growing societal problem, with implications for acad

Whose Data, Whose Benchmark? A User-Centric Framework for Auditing Evaluation Resources

model-releasesarxiv-cs-cl

arXiv:2610.19268v1 Announce Type: new Abstract: Benchmarks shape how model capabilities are measured and interpreted, yet their scores can obscure whose conventions, contexts, and judgments define suc

Why Do VLMs Fail at Remote Physiological Measurement? Rethinking with Physiological Grounding and Numerical Alignment

arXiv:2610.19052v1 Announce Type: new Abstract: Video-based remote physiological measurement (RPM) has broad applications, while Vision-Language Models (VLMs) provide a promising opportunity to enable

Words to World: Benchmarking LLMs in Interactive Physical Environments

arXiv:2610.15228v1 Announce Type: new Abstract: Words are increasingly becoming an interface for action: large language models (LLMs) can now invoke tools, operate devices, and make decisions that aff

WorldMemBench: A Comprehensive Benchmark for Memory of Video World Models

arXiv:2610.19063v1 Announce Type: new Abstract: As video models enable longer and more realistic interactive experiences, maintaining a world consistent with its history becomes essential. This requir

XL-SafetyBench: A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity

arXiv:2605.05662v2 Announce Type: replace-cross Abstract: Current LLM safety benchmarks are predominantly English-centric and often rely on translation, failing to capture country-specific harms. More

Your Transformer Is Secretly Elastic

arXiv:2610.20588v1 Announce Type: new Abstract: Scaling up transformers has produced models with broad capabilities, deployed across heterogeneous hardware and fluctuating workloads. Yet, model famili

3D-VITAL: Visibility-aware Identity Training from Artificial Liftings of 3D Reconstruction model for Cross-View Object Re-Identification

arXiv:2610.16692v1 Announce Type: new Abstract: We address the Cross-View Object Re-Identification (ReID) task, aiming to match identities across drastically different viewpoints. We focus on Single-V

A Geometric Perspective on Reward Function Updates in Inverse Reinforcement Learning

arXiv:2610.14041v1 Announce Type: new Abstract: Inverse Reinforcement Learning (IRL) is classically solved using Lagrangian optimisation, by jointly optimising a primal-dual problem with gradient desc

A Hybrid Gaussian Process-Extreme Gradient Boosting Machine Learning Framework for Robust Knockdown Factor Prediction and Reliability-Based Design of Thin Spherical Shell Caps

arXiv:2610.15862v1 Announce Type: new Abstract: Elastic buckling remains a critical concern in the design of deep spherical shell caps, given that experiments reveal a significant reduction of critica

A Multi-Task Deep Learning Framework for Pose-Invariant Face Recognition and Facial Landmark Localization

arXiv:2610.16849v1 Announce Type: new Abstract: Face recognition systems often experience performance degradation under large pose variations due to changes in facial appearance and visibility of disc

A Nonlinear Time-Series Theory for Constant-step SGD with Momentum

arXiv:2610.16034v1 Announce Type: cross Abstract: Constant-step stochastic gradient descent with momentum (SGDM) augments the parameter recursion with a momentum state that carries geometrically decay

A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding

arXiv:2610.15666v1 Announce Type: new Abstract: Converting natural-language instructions into executable action plans conditioned on a scene image is a core capability for embodied human-robot interac

A Plausible Future Is Not a Causal Future: Can Video Models Generate How the World Unfolds?

arXiv:2610.15562v1 Announce Type: new Abstract: Large-scale video generation models are increasingly viewed as a promising path toward world models, yet their ability to capture causally coherent phys

A Reinforcement Learning Framework for Safety-Aware Haptic Shared Control in Surgical Robotics

arXiv:2610.15422v1 Announce Type: new Abstract: Haptic shared control in surgical robotics combines human-side and robot-side forces at a shared end effector while preserving operator involvement. How

A text-guided vision model for enhanced recognition of small instances

arXiv:2602.19503v2 Announce Type: replace Abstract: As drone-based object detection technology continues to evolve, the demand is shifting from merely detecting objects to enabling users to accurately

AeroChem: Closed-loop Physics-Informed State Space Modeling for Long-term Chemically-Reactive Air Quality Forecasting--Extended Version

arXiv:2610.16630v1 Announce Type: new Abstract: Accurate long-term air quality forecasting is challenging due to long-range transport, meteorological variability, and nonlinear chemical reactions unde

AffectWorld: Benchmarking Emotion-Driven Future World Prediction

arXiv:2610.18305v1 Announce Type: new Abstract: The world encompasses both physical environments and human actors. Predicting its evolution requires understanding both physical laws and how emotions s

Agaram 2.5B: The First Tamil-First Language Model Trained from Scratch with Tool Calling. A Playbook for Under-Represented Languages

arXiv:2610.18420v1 Announce Type: cross Abstract: We trained Agaram 2.5B, a 2.5-billion-parameter Tamil-English language model, from scratch on about 50 billion tokens (58% Tamil, the rest English, ma

agent-risk: Risk Assessment for Changes to AI Agents

arXiv:2610.16280v1 Announce Type: cross Abstract: Before changing a deployed AI agent (a stricter safety gate, a new model), organizations must approve the change, starting from existing logs. Extendi

Agentic-MatriBO: Capability-Compiled Agentic Bayesian Optimization for Materials and Chemical Design

arXiv:2610.17832v1 Announce Type: new Abstract: Materials and chemical optimization must choose the next synthesis, characterization, or high-fidelity simulation from sequential observations under a l

AI Discovery in Combinatorics: From Problems to Solutions and Back to Bigger Problems

arXiv:2610.16555v1 Announce Type: cross Abstract: We introduce qtBench, a benchmark of 29 open problems in algebraic combinatorics. These problems ask for a simple combinatorial algorithm that explain

AMemOps: Evaluating Memory Updates in Long Audio Streams

arXiv:2610.18652v1 Announce Type: cross Abstract: Audio memory must recognise recurring sources across acoustic changes while keeping their attributes up to date. Overall accuracy does not reveal how

An Open MuJoCo Simulation Framework for a Quadrotor Carrying a Tendon-Driven Soft Continuum Arm

arXiv:2610.15308v1 Announce Type: new Abstract: Combining aerial robots with soft continuum manipulators promises safe, compliant interaction with the environment, but the coupled dynamics of a free-f

AnolisVLA: Lightweight Vision-Language-Action Model with Deep State Space Models for Mobile Manipulation

arXiv:2603.15046v2 Announce Type: replace Abstract: In this study, we address the problem of language-guided robotic manipulation, where a robot is required to manipulate a wide range of objects based

APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation

arXiv:2610.18097v1 Announce Type: new Abstract: Post-training is crucial for improving text-to-image models, yet existing pipelines typically rely on manually curated training data and fixed training

Artificiality's First Exam: An LLM-Referenced C-test for Supraintelligence

arXiv:2610.14005v1 Announce Type: cross Abstract: Under the accelerated pace of AI development, any benchmark whose difficulty is calibrated with humans or current AI systems becomes circular, or satu

Ascent Conditions for Length-Normalized Single-Rollout Policy Updates

arXiv:2610.14670v1 Announce Type: new Abstract: Dividing each trajectory's score contribution by its realized length can change the direction of a reward-centered policy update. In a finite trajectory

Asynchronous Sharpness-Aware Minimization For Fast and Accurate Deep Learning

arXiv:2503.11147v2 Announce Type: replace Abstract: Sharpness-Aware Minimization (SAM) is an optimization method that improves the generalization performance of machine learning models. Despite its ef

Attribute-Centric Vision-Language Alignment for Fine-Grained Gait Understanding

arXiv:2610.14589v1 Announce Type: new Abstract: Walking sequences reveal human-interpretable attributes related to body structure, posture, and motion. Gait attribute recognition provides a concrete r

ATTUNE: Agentic Throughput Tuning for LLM Training

arXiv:2610.17528v1 Announce Type: cross Abstract: Training recipes are tuned by hand for one model, cluster and workload, and every new model, accelerator, framework version or dataset means tuning ag

Auditing Failure Attribution: Label Predictability and Judge Behavior

arXiv:2610.17747v1 Announce Type: cross Abstract: Failure-attribution benchmarks ask an LLM judge which step or agent caused a failure. A high score should mean the judge checked the faulty step again

AURORA-KITTI: Any-Weather Depth Completion and Denoising

arXiv:2603.14701v2 Announce Type: replace Abstract: Robust depth completion is fundamental to real-world 3D scene understanding, yet existing RGB--LiDAR fusion methods degrade significantly under adve

AutoEnvScaling: Automating the Data Flywheel with Terminal Agents

arXiv:2610.14163v1 Announce Type: cross Abstract: Terminal agents solve tasks in software engineering and scientific research by executing commands in a terminal. Training them via reinforcement learn

Automatic Thematic Indexing of Large Literary Corpora: A Machine Learning Approach to Voltaire's Complete Works

arXiv:2607.09316v2 Announce Type: replace-cross Abstract: Thematic indexing -- the practice of assigning structured conceptual labels to sections of text -- is essential to scholarly access in large-s

Autoregressive Decoding as a Martingale: Characterizing the Stochastic Dynamics of LLM Generation

arXiv:2610.16041v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of language tasks. At their core, autoregressive LLMs are conditional

Backward Conformal Prediction under Covariate Shift

arXiv:2610.16048v1 Announce Type: new Abstract: Backward conformal prediction (BCP) fixes the size of a prediction set and estimates its miscoverage, but assumes calibration and test data are exchange

BandPC: Learning Residual-Band Preconditioner Combinations for Flexible Conjugate Gradient Solvers

arXiv:2609.37140v1 Announce Type: cross Abstract: The conjugate gradient (CG) method is a classical iterative solver for sparse symmetric positive definite (SPD) linear systems, but its convergence st

BARTER: Compact Dynamic Sparse Training with Standard Dense Kernels

arXiv:2610.16147v1 Announce Type: new Abstract: Dynamic sparse training (DST) aims to reduce training costs while maintaining accuracy. Existing DST methods mask out parameters but keep matrix dimensi

BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation

arXiv:2610.15330v1 Announce Type: new Abstract: Accurate brain tumor segmentation from magnetic resonance imaging (MRI) is essential for diagnosis and treatment planning; however, manual delineation i

Bayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic Models

arXiv:2510.06439v2 Announce Type: replace Abstract: Hyperparameter tuning is a challenging problem especially when the system itself involves uncertainty. Due to noisy function evaluations, optimizati

Benchmarking Deep Learning Models for Anomaly Detection in Real-World Cloud Telemetry

arXiv:2610.15818v1 Announce Type: new Abstract: Modern cloud platforms generate high-dimensional, noisy telemetry from thousands of microservices. Unlike classical anomaly detection benchmarks, cloud

Benchmarking Interaction-Oriented Aerial Mobility across Heterogeneous Environments

arXiv:2610.18381v1 Announce Type: new Abstract: Aerial mobile manipulation requires unmanned aerial vehicles (UAVs) to traverse heterogeneous environments such as indoor and outdoor domains, and conne