Search: “models”

Conduct Under Pressure: What Sixty Language Models Do When a User Pushes

arXiv:2609.25447v1 Announce Type: new Abstract: We study what LLMs do when a user applies pressure in an uncomfortable situation: a user insists, begs, flatters or grieves, and the model gives up a co

researcharxiv-cs-cl

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LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

DGX agent

arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol

safetyarxiv-cs-ai

23 Sept 2026

Tutorials

Lifelong Learning of Video Diffusion Models From a Single Video Stream

arXiv:2406.04814v4 Announce Type: replace-cross Abstract: Video diffusion models can enable embodied agents to anticipate plausible futures from the recent past, but they are typically trained offline

tutorialsarxiv-cs-lg

Mean Velocity Matching: Rethinking Generative Dynamics in Diffusion Models

arXiv:2609.25444v1 Announce Type: new Abstract: This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range

applicationsarxiv-cs-ai

Rethinking Length-Based Training: Batch Composition and Loss Normalization in Speech Token Language Models

arXiv:2609.25890v1 Announce Type: new Abstract: Short-to-long training is a simple curriculum for speech models, but its gains can be difficult to interpret. In speech token language models, length-ba

safetyarxiv-cs-cl

A Comparative Framework for Evaluating Foundation Models on Tabular Data: A Case Study in Healthcare

arXiv:2609.22154v1 Announce Type: new Abstract: Tabular data is the most common format in clinical practice, encompassing laboratory results, medication records, diagnostic codes, and patient demograp

applicationsarxiv-cs-lg

BackdoorVLM: A Benchmark for Backdoor Attacks and Defenses on Vision-Language Models

arXiv:2511.18921v2 Announce Type: replace Abstract: Backdoor attacks undermine the reliability and trustworthiness of machine learning systems by injecting hidden behaviors that can be maliciously act

Beyond Appearance Shifts: Task-Semantic Action Calibration for VLA Models

arXiv:2609.23650v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved strong performance in embodied manipulation, but still lack a clear mechanism to balance behavioral

Hierarchical Prompt Learning for Hyperbolic Vision-Language Models

arXiv:2609.24276v1 Announce Type: new Abstract: Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstre

Is Imagination Derived from Hallucination? A Cross-Taxonomy Evaluation of Imagination and Hallucination in Large Language Models

arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative co

Leveraging Inference-Time Compute for Diffusion Models via Global Scheduling of Denoising Trajectories

arXiv:2609.22867v1 Announce Type: new Abstract: Diffusion models generate a sample by traversing a denoising trajectory, a sequence of stochastic noise-reduction steps that transforms pure noise into

Matched-Input Estimates Differ in Sign Across Architectures: Auditing EEG Foundation Models on Motor Imagery

arXiv:2609.23924v1 Announce Type: new Abstract: Pretrained EEG foundation models are increasingly proposed as general-purpose encoders for brain-computer interfaces, yet recent benchmarks disagree abo

PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models

arXiv:2609.23574v1 Announce Type: cross Abstract: In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting.

PETR: Prompt Ensembling with Training-free Routing for Vision-Language Models

arXiv:2609.23600v1 Announce Type: new Abstract: Prompt learning efficiently adapts vision-language models (VLMs) to downstream tasks, but gains on seen classes often come at the expense of generalizat

Representation-guided in-context learning for medical image interpretation with multimodal large language models

arXiv:2609.24057v1 Announce Type: cross Abstract: Medical image interpretation is central to diagnosis and care, yet adapting general-purpose multimodal large language models (MLLMs) often requires re

Watching Quantum Models Think: Hilbert-Space Interpretability in Quantum Transformer Blocks

arXiv:2609.23016v1 Announce Type: cross Abstract: Deep learning models are powerful but opaque. As quantum machine learning matures, the field faces a defining choice: build quantum models that are eq

Samsone: A Family of Open Small Audio Language Models for On-Device Inference

arXiv:2609.21666v1 Announce Type: cross Abstract: The success of Large Audio Language Models has driven the development of massive multimodal networks exceeding billions of parameters. However, the de

local-aiarxiv-cs-ai

21 Sept 2026

Compact Vision Models for Iris Presentation Attack Detection under Presentation Attack Instrument Shift and Environmental Degradation

arXiv:2609.20386v1 Announce Type: new Abstract: Iris presentation attack detection (PAD) is security-critical when a subsystem that appears reliable during development encounters presentation attack i

Comparison of Image Processing Models in Quark Gluon Jet Classification

arXiv:2602.00141v2 Announce Type: replace-cross Abstract: Quark-gluon discrimination provides a useful test case for studying how different machine-learning architectures learn the spatial structure o

local-aiarxiv-cs-cv

Conservation Buys Stability and Factoring Buys Counterfactuals in Physical World Models

arXiv:2609.19674v1 Announce Type: new Abstract: A learned simulator can reproduce its training conditions accurately yet fail in two distinct ways once those conditions change. Over long rollouts, sma

DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation

arXiv:2609.20649v1 Announce Type: cross Abstract: Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots

safetyarxiv-cs-cv

dQwen3.5: Hybrid-Attention Diffusion Language Models

arXiv:2609.20751v1 Announce Type: new Abstract: Adapting a pretrained autoregressive (AR) model is a cost-efficient route to a diffusion language model (DLM). While nearly all such adaptations start f

researcharxiv-cs-cl

From Models to Systems: A Comprehensive Survey of Efficient Multimodal Learning

arXiv:2609.19445v1 Announce Type: cross Abstract: The rapid expansion of multimodal models has surfaced formidable bottlenecks in computation, memory, and deployment, catalyzing the rise of Efficient

applicationsarxiv-cs-ai

GAVEL: Graph World Models for Verified and Efficient Long-Horizon LLM Task Planning

arXiv:2609.19315v1 Announce Type: cross Abstract: Large language models (LLMs) provide a flexible interface for long-horizon robot planning, but generated plans often fail to respect embodiment constr

researcharxiv-cs-ai

Music Hallucination in Audio-Language Models: A Hierarchical Formulation and Empirical Study

arXiv:2609.20195v1 Announce Type: cross Abstract: Audio-language models increasingly generate confident music descriptions that are unsupported by the input audio. We present, to our knowledge, the fi

safetyarxiv-cs-ai

On-Demand Attention: Language Models Know When to Recall

arXiv:2609.20734v1 Announce Type: new Abstract: Reasoning and agentic workloads increasingly demand efficient long-context inference. Yet full-attention decoding reads the growing history at every ste

Predict Before You Deploy: Offline Prediction of Quantization-Induced Task Degradation for World Action Models

model-releasesarxiv-cs-ai

arXiv:2609.19441v1 Announce Type: cross Abstract: World action models (WAMs) rely on video-generation backbones, requiring substantial memory and compute for deployment. Post-training quantization red

Score-based diffusion models for severely ill-posed problems in diffuse optical tomography

arXiv:2602.03449v2 Announce Type: replace-cross Abstract: Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems, enabling high-quality rec

local-aiarxiv-cs-lg

Selective Cotton Boll Localization for Robotic Harvesting: Evaluation of Deep Learning Vision Models Under Field Conditions

arXiv:2609.19592v1 Announce Type: new Abstract: This study developed and evaluated a deep-learning-based perception framework for selective robotic cotton picking. The dataset contained 1,008 annotate

local-aiarxiv-cs-cv

Tutorials

Tailored to you: longitudinal effects of personalising language models

arXiv:2609.20077v1 Announce Type: new Abstract: Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse use

tutorialsarxiv-cs-ai

Attention Dispersion as a Diagnostic Signal for Hallucination in Large Language Models

arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional

safetyarxiv-cs-cl

Benchmarking Tabular Foundation Models as Surrogates in Expensive Evolutionary Optimization

arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re

Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation

arXiv:2502.14254v3 Announce Type: replace-cross Abstract: Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, en

Not All Layers Need Tuning: Diagnosing and Directing Adaptation in Vision-Language-Action Models

arXiv:2609.18084v1 Announce Type: cross Abstract: Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to ev

The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models

model-releasesarxiv-cs-ai

arXiv:2408.07702v2 Announce Type: cross Abstract: Schema linking is a crucial step in Text-to-SQL pipelines. Its goal is to retrieve the relevant tables and columns of a target database for a user's q

The Unbearable Weight: Scaling Models and Methods for UAV Audio Classification

arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp

Veo-Act: Enhancing VLA Policies with Frontier Video Models

arXiv:2604.04502v2 Announce Type: replace Abstract: Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video genera

safetyarxiv-cs-ro

What Counts as Strategic Reasoning? A Systematic Mapping of Chess Research on Humans, Engines, and Language Models

arXiv:2609.18286v1 Announce Type: new Abstract: Chess has long served as a model domain for studying search, expertise, decision-making, and artificial intelligence. The emergence of large language mo

Generating Individual Travel Diaries Using Large Language Models Informed by Census and Land-Use Data

arXiv:2509.09710v3 Announce Type: replace-cross Abstract: This study introduces a Large Language Model (LLM) scheme for generating key attributes of travel diaries in agent-based transportation models

High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics

arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,

Hardware

High-Performance Tensor Formulation of the Viterbi Algorithm for Hidden Semi-Markov Models

arXiv:2609.16500v1 Announce Type: new Abstract: Hidden Semi-Markov Models (HSMMs) are fundamental probabilistic models widely adopted across diverse domains, from computational biology to finance and

hardwarearxiv-cs-lg

Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation

arXiv:2606.18960v3 Announce Type: replace Abstract: Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experi

safetyarxiv-cs-cv

Modality-Autoregressive World-Action Models

arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as

applicationsarxiv-cs-ro

A primer on evaluation methods for large language models in healthcare

arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and

An Incomplete Loop: Deductive, Inductive, and Abductive Reasoning in Language Models

arXiv:2404.03028v4 Announce Type: replace Abstract: Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in

Discovery Foundation Models: Toward Open-Ended Discovery Intelligence

arXiv:2609.15973v1 Announce Type: new Abstract: Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome fe

agentsarxiv-cs-cl

Tutorials

ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models

arXiv:2609.15089v1 Announce Type: new Abstract: Empathetic response generation in spoken dialogue systems requires both accurate emotion perception and appropriate emotion regulation. Grounded in psyc

tutorialsarxiv-cs-ai