Search: “models”

Patient-level validation of a foundation-model pipeline for pediatric lung sounds: physician-annotated adventitious events are recognized, disease groups are not reliably predicted

arXiv:2603.15688v2 Announce Type: replace-cross Abstract: Background: Lung-sound classifiers are usually evaluated on recording- or event-level splits, although each child contributes many recordings.

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Agents

PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving

arXiv:2602.12029v2 Announce Type: replace Abstract: Multi-agent systems increasingly orchestrate multiple specialized language models to solve complex real-world problems, often invoking them over a s

agentsarxiv-cs-lg

QwenGyre: An Elastic Reinforcement Learning Framework for Training xLong-Horizon Agents

arXiv:2609.33848v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly undertake extreme-long (xlong) horizon tasks, where a single execution can span hours, hundreds of model-

ReFM: Semantic-Aware Refinement Flow Model for Motion Retargeting

arXiv:2609.32068v1 Announce Type: new Abstract: Motion retargeting transfers motion across characters with different skeletal structures while preserving semantic intent and physical plausibility. Des

researcharxiv-cs-cv

Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios

arXiv:2609.35086v1 Announce Type: new Abstract: In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture

Retrospective Distillation Attribution via Normalized Response Similarity

arXiv:2609.32749v1 Announce Type: cross Abstract: Model distillation transfers capabilities through supervised fine-tuning (SFT) on teacher responses, often collected from commercial APIs, raising que

Scaling Versatile 3D Assets Editing with a Million-Scale Dataset

model-releasesarxiv-cs-cv

arXiv:2609.34271v1 Announce Type: new Abstract: Although recent 3D generative models produce increasingly realistic assets, controllable 3D asset editing remains challenging. Existing methods are limi

SCLATE: a Substrate for Continual-Learning Agent Training and Evaluation

arXiv:2609.32391v1 Announce Type: cross Abstract: Continual-learning agents are systems of models, harnesses, and memory operating over long multi-session horizons. Evaluating and training them requir

Structured Latent Modeling for Supervised Multimodal Information Decomposition

arXiv:2609.35502v1 Announce Type: new Abstract: Multimodal prediction relies on diverse forms of evidence: information repeated across modalities, cues specific to a single source, and complex cross-m

Sub-Model Short-Term Memory Convolutions for Keyword Spotting Systems on Device

arXiv:2609.35005v1 Announce Type: cross Abstract: Keyword Spotting (KWS) is becoming increasingly important as voice-controlled devices grow more widespread. While voice interaction with smartphones a

Unified Visual-Tactile-Action Modeling from Human Demonstrations for Dexterous Manipulation

arXiv:2609.34182v1 Announce Type: new Abstract: Dexterous manipulation requires tactile feedback.However, robot tactile demonstrations are difficult to scale,because dexterous-hand teleoperation provi

researcharxiv-cs-ro

When Can We Trust the Sparse Lens? A Certification Framework for SAE Faithfulness

arXiv:2606.18383v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) are increasingly used to study internal representations in language models (LMs), but it remains unclear when an SAE-base

When VLMs Trust Context: Evaluating Scene Text Recognition under Misleading Context

model-releasesarxiv-cs-cv

arXiv:2609.34781v1 Announce Type: new Abstract: Vision-language models (VLMs) can read text in natural scenes, but their predictions may be influenced by the surrounding context. When the printed text

Does Thinking Help Fairness? Reasoning Tokens Resolve Some Biases but Create More

arXiv:2609.30768v1 Announce Type: new Abstract: Thinking in reasoning language models (RLMs) has been subject to debate on whether it resolves or amplifies bias. Prior works have shown competing concl

Geometric Inconsistency Localization in Multi-View Image Sets

arXiv:2609.31247v1 Announce Type: cross Abstract: Novel view synthesis (NVS) models can produce realistic new views of the same scene from different viewpoints. However, these generated views are not

MoSAR: Mixture of Semantic Attention Regimes for Learning Adaptive and Approximable Attention Geometries

arXiv:2609.31261v1 Announce Type: cross Abstract: The quadratic complexity of dense self-attention remains a central bottleneck for long-context language modeling. Many efficient alternatives address

Agents

Onboard Wind-Preview Model Predictive Control Using Pitot-Static Sensing for Multirotor UAVs

arXiv:2609.31185v1 Announce Type: new Abstract: Effective wind gust rejection and stable hovering are critical for the outdoor operation of autonomous drones. However, existing gust rejection methods

agentsarxiv-cs-ro

Same Text, Different Numbers: The Divergence of LLM-Based Measures

arXiv:2609.31013v1 Announce Type: new Abstract: Researchers increasingly use generative large language models (LLMs) to convert corporate text into empirical variables. We examine the extent to which

Strategic Self-Consistency

arXiv:2609.30352v1 Announce Type: cross Abstract: Self-consistency has become a popular technique for enhancing the reasoning abilities of large language models by generating multiple reasoning paths

TRACE: Temporal Audit and Condition-aware Evaluation of Streaming Video Understanding

arXiv:2609.30670v1 Announce Type: new Abstract: Streaming video understanding requires models to interpret evidence as it arrives, yet current evaluations often report task scores without specifying w

A Nearly Quadratic Lower Bound for Linear Optimization over Convex Bodies in the Membership Oracle Model

arXiv:2609.30215v1 Announce Type: cross Abstract: We prove nearly quadratic lower bounds for randomized algorithms for linear optimization and uniform sampling over convex bodies in the membership ora

AgenticCADedit: A Stateful, Tool-Mediated Agentic Approach to Multimodal 3D CAD Editing

model-releasesarxiv-cs-cv

arXiv:2609.29621v1 Announce Type: new Abstract: Computer-aided design is central to industrial manufacturing, and much of a designer's daily work consists of editing existing models from multimodal re

Automated Regulatory Compliance Question Answering in Financial Services with Domain-Adapted Retrieval-Augmented Generation

arXiv:2609.30009v1 Announce Type: cross Abstract: Financial institutions operate under dense, frequently amended rulebooks, and answering a compliance question correctly requires not only fluency but

Automatic Harness Evolution for Hardware Design Verification: Can LLMs Consolidate Gains Across Discovered Harnesses?

arXiv:2609.28908v1 Announce Type: cross Abstract: Agent behavior depends on the harness surrounding a language model, but it remains unclear whether language models can reliably improve such harnesses

Safety

It's the Geometry, Not the Model: Effective Rank and Subspace Alignment in Functional Connectivity Classification

arXiv:2609.29932v1 Announce Type: cross Abstract: Resting-state functional connectivity (FC) is widely used to classify brain phenotypes and disorders. Most pipelines use the full connectome and seek

safetyarxiv-cs-cv

Limited Structural Reliability in Public Educational Prediction Benchmarks: A Four-Dimension Audit of Seven Datasets

arXiv:2609.29625v1 Announce Type: new Abstract: Across seven public educational prediction datasets, three passed all four pre-modeling reliability checks; the remaining four either failed group-aware

Agents

Novelty Adaptation Through Hybrid Large Language Model (LLM)-Symbolic Planning and LLM-guided Reinforcement Learning

arXiv:2603.11351v2 Announce Type: replace-cross Abstract: In dynamic open-world environments, autonomous agents often encounter novelties that hinder their ability to find plans to achieve their goals

agentsarxiv-cs-ai

Safety

Persuaded, Not Informed: Incentive-Misaligned Witnesses Defeat In-Context Grounding

arXiv:2609.28854v1 Announce Type: cross Abstract: Language-model agents increasingly answer questions over customer-relationship management (CRM) records, such as whether to qualify a sales lead. We i

safetyarxiv-cs-ai

Revalidation Beats Stateful Routing for Scientific Surrogates Under Distribution Shift

arXiv:2609.29715v1 Announce Type: cross Abstract: Surrogate models are often chosen during development and then left in place as new measurements arrive. That practice becomes risky when noise, input

Sequential Confidence Sets for Coverage-Constrained Conformal Model Selection

arXiv:2609.28522v1 Announce Type: cross Abstract: Modern conformal forecasting systems often maintain several adaptive pipelines that differ in base forecasters, conformity scores, calibration windows

Small yet Assistive: Spatially-Aware Post-Training for Low Vision

arXiv:2609.28757v1 Announce Type: cross Abstract: An estimated 1 billion people worldwide live with vision impairment, yet current vision-language models (VLMs) produce descriptions too vague for safe

Stale Does Not Mean Unsafe: Guard Precision for Tool-Using LLM Agents under Infrastructure State Races

arXiv:2609.29522v1 Announce Type: new Abstract: Tool-using language-model agents increasingly mutate schedulers, data pipelines, object stores, and access-control systems. Between an agent's read and

Type-Safe Is Not Error-Free: A Constrained Decision Head Follows the Option Name, Not the Rubric Bound to It

arXiv:2609.26758v2 Announce Type: replace Abstract: Typed decision models are built for settings where model outputs are consumed directly by software. Instead of generating free-form text, they retur

An Open Pipeline and Dashboard for Systemic-Risk Evidence under the EU AI Act's Code of Practice

arXiv:2609.28335v1 Announce Type: new Abstract: Claims about AI safety reach audiences well beyond the AI community, yet many rely on opaque evidence or static assessments, when supporting evidence is

Experts Rise Where LLMs Disagree: Using Cross-Model Disagreement to Target Expert Effort in LLM Codebook Revision for Large-Scale Annotation

arXiv:2609.26926v1 Announce Type: cross Abstract: Large-scale text annotation brings expert insight to millions of documents, often through a codebook that AI annotators follow. Developing a robust co

Field-of-View Extension in Dental Cone-Beam CT via Implicit Neural Representations and Diffusion Model-Based Refinement

arXiv:2609.28110v1 Announce Type: cross Abstract: Dental cone-beam computed tomography (CBCT) systems often employ detector configurations that provide a truncated field of view (FOV) that only captur

Local Ai

From greenhouse climate to individual leaves: an organ-resolved model of lettuce growth

arXiv:2609.27118v1 Announce Type: new Abstract: Greenhouse climate management aims to improve crop production while limiting energy use. This requires knowing how a crop will respond before conditions

local-aiarxiv-cs-cv

Inverse Problems Conditioned on Observation Ensembles: Applications and Methods

arXiv:2601.22029v2 Announce Type: replace Abstract: We introduce a new multivariate statistical problem that we refer to as the Ensemble-conditioned Inverse Problem (EIP). The aim of EIP is to invert

Prompt, Probe, Train, or Annotate? Single-camera sports video understanding in amateur settings

arXiv:2609.28049v1 Announce Type: cross Abstract: Video understanding is usually benchmarked on curated, single-actor, or professionally filmed clips, and a strong score there is routinely read as evi

Realize What Matters: Principled Context Representation for Large-Scale Reasoning

arXiv:2609.27173v1 Announce Type: new Abstract: Solving complex tasks in domains such as science, medicine, law, and finance often requires assembling interdependent information scattered across vast,

Repurposing Pre-trained LLMs as High Fidelity Continuous Text Autoencoders

arXiv:2609.27248v1 Announce Type: new Abstract: Next-token prediction has enabled highly fluent autoregressive language models, but it represents global structure only indirectly through sequential fa

Water Surface Swimming in a Centipede and its Robophysical ModeL

arXiv:2609.27088v1 Announce Type: new Abstract: Elongate multi-legged robots use coordinated body waves and distributed legs to move through cluttered terrestrial environments. However, as housing act

researcharxiv-cs-ro

Safety

Which Objectives Need a Dial? Predicting Objective Conflict and Covering Trade-offs in Steerable Pluralistic Alignment

arXiv:2609.26929v1 Announce Type: new Abstract: People hold diverse, sometimes conflicting values, so no single aligned model can satisfy everyone. Pluralistic alignment therefore calls for steerable

safetyarxiv-cs-ai

Compared to What? A Human-Anchored Security Benchmark for LLM-Generated Infrastructure-as-Code

arXiv:2608.28021v2 Announce Type: replace-cross Abstract: Large language models increasingly author Infrastructure-as-Code (IaC), where one insecure default is provisioned straight into production. Pr

Deep Generative Crystal Structure Prediction: A Benchmark Study and a Controlled Test of Prototype Dependence

arXiv:2609.26502v1 Announce Type: cross Abstract: Deep generative models are widely reported to enable de novo crystal structure prediction (CSP), but their capability has not been measured consistent

Do Synthetic Personas Predict Real Audience Response? A Sim-to-Real Study Where a No-Persona Baseline Beats Persona-Based Copy Simulation

arXiv:2609.25010v1 Announce Type: cross Abstract: Marketers increasingly use large language models (LLMs) as 'synthetic personas' to predict how an audience will react to a piece of copy before it shi

Exposing Blind Spots in Deep Imbalanced Regression Evaluation

arXiv:2609.25152v1 Announce Type: new Abstract: Deep Imbalanced Regression (DIR) addresses a common failure mode of regression models: target distributions are highly non-uniform, causing models to pe

mbariml: a curation pipeline for turning deep-sea imagery and video into object-detection training data

arXiv:2609.25500v1 Announce Type: new Abstract: Training data quantity and quality greatly affect object detection model performance, regardless of model architecture. When using object detection mode

researcharxiv-cs-cv