Search: “models”

Exploring Applications of Transfer-State Large Language Models: Cognitive Profiling and Socratic AI Tutoring

arXiv:2604.27454v1 Announce Type: new Abstract: Large language models (LLMs) sometimes exhibit qualitative shifts in response style under sustained self-referential dialogue conditions (Berg et al., 2

safetyarxiv-cs-cl

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Research

Learning to Spend: Model Predictive Control for Budgeting under Non-Stationary Returns

DGX agent

arXiv:2604.27186v1 Announce Type: cross Abstract: We study finite-horizon budget allocation as a closed-loop economic control problem and evaluate receding-horizon Model Predictive Control (MPC) relat

researcharxiv-cs-ai

1 May 2026

Predicting Upcoming Stuttering Events from Three-Second Audio: Stratified Evaluation Reveals Severity-Selective Precursors, and the Model Deploys Fully On-Device

model-releasesarxiv-cs-lg

arXiv:2604.27279v1 Announce Type: cross Abstract: Audio-based stuttering systems to date have been trained for detection -- what disfluency is present now -- leaving prediction, the capability needed

Proactive Dialogue Model with Intent Prediction

arXiv:2604.27379v1 Announce Type: new Abstract: Dialogue models are inherently reactive, responding to the current user turn without anticipating upcoming intents, which leads to redundant interaction

Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling

arXiv:2604.28075v1 Announce Type: cross Abstract: Recent research has shown that filtering massive English web corpora into high-quality subsets significantly improves training efficiency. However, fo

Sampler-Robust Optimization under Generative Models

arXiv:2604.27447v1 Announce Type: cross Abstract: Modern stochastic optimization pipelines increasingly rely on learned generative models to represent uncertainty, while downstream decisions are evalu

Semantic Structure of Feature Space in Large Language Models

arXiv:2604.27169v1 Announce Type: new Abstract: We show that the geometric relations between semantic features in large language models' hidden states closely mirror human psychological associations.

Simulating clinical interventions with a generative multimodal model of human physiology

arXiv:2604.27899v1 Announce Type: new Abstract: Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine.

The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text

arXiv:2604.27673v1 Announce Type: new Abstract: We introduce Target-Event-Agent Networks (TEA Nets) as a computational framework to extract subjects (``Agents'), verbs (``Events'), and objects (``Targ

Vision-Language Models Mistake Head Orientation for Gaze Direction: Nonverbal Conversation Cues

arXiv:2506.05412v3 Announce Type: replace-cross Abstract: Where someone looks is a nonverbal communication cue that children and adults readily use. How well can Vision-Language Models (VLMs) infer ga

safetyarxiv-cs-cl

A Dual-Task Paradigm to Investigate Sentence Comprehension Strategies in Language Models

arXiv:2604.26351v1 Announce Type: new Abstract: Language models (LMs) behave more like humans when their cognitive resources are restricted, particularly in predicting sentence processing costs such a

ComboStoc: Combinatorial Stochasticity for Diffusion Generative Models

arXiv:2405.13729v3 Announce Type: replace-cross Abstract: In this paper, we study an under-explored but important factor of diffusion generative models, i.e., the combinatorial complexity. Data sample

Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models

arXiv:2604.26503v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in synthesizing complex static and temporal visuals, a breakthrough largely driven by Classifier-Free

safetyarxiv-cs-cv

DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training

arXiv:2604.26256v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a critical paradigm for LLM post-training, yet the rollout phase -- accounting for 50--80% of total step time --

safetyarxiv-cs-lg

From Prompt Risk to Response Risk: Paired Analysis of Safety Behavior of Large Language Model

arXiv:2604.26052v1 Announce Type: new Abstract: Safety evaluations of large language models (LLMs) typically report binary outcomes such as attack success rate, refusal rate, or harmful/not-harmful re

safetyarxiv-cs-cl

HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models

arXiv:2604.26139v1 Announce Type: new Abstract: Diffusion large language models generate text through multi-step denoising, where hallucination signals may emerge throughout the trajectory rather than

LLM-Flax : Generalizable Robotic Task Planning via Neuro-Symbolic Approaches with Large Language Models

model-releasesarxiv-cs-ro

arXiv:2604.26569v1 Announce Type: new Abstract: Deploying a neuro-symbolic task planner on a new domain today requires significant manual effort: a domain expert must author relaxation and complementa

Stochastic Scaling Limits and Synchronization by Noise in Deep Transformer Models

arXiv:2604.26898v1 Announce Type: cross Abstract: We prove pathwise convergence of the layerwise evolution of tokens in a finite-depth, finite-width transformer model with MultiLayer Perceptron (MLP)

Text-Utilization for Encoder-dominated Speech Recognition Models

arXiv:2604.26514v1 Announce Type: cross Abstract: This paper investigates efficient methods for utilizing text-only data to improve speech recognition, focusing on encoder-dominated models that facili

Understanding DNNs in Feature Interaction Models: A Dimensional Collapse Perspective

arXiv:2604.26489v1 Announce Type: new Abstract: DNNs have gained widespread adoption in feature interaction recommendation models. However, there has been a longstanding debate on their roles. On one

BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

model-releasesarxiv-cs-cv

arXiv:2604.24999v1 Announce Type: new Abstract: Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understa

Knowledge-Data Dually Driven Paradigm for Accurate Landslide Susceptibility Prediction under Data-Scarce Conditions Using Geomorphic Priors and Tabular Foundation Model

arXiv:2604.25196v1 Announce Type: new Abstract: Landslide susceptibility prediction is critical for geohazard risk assessment and mitigation. Conventional data-driven paradigm achieves high predictive

Learning biophysical models of gene regulation with probability flow matching

arXiv:2604.25062v1 Announce Type: cross Abstract: Cellular differentiation is governed by gene regulatory networks, the high-dimensional stochastic biochemical systems that determine the transcription

Tutorials

UniSER: A Foundation Model for Unified Soft Effects Removal

arXiv:2511.14183v3 Announce Type: replace Abstract: Digital images are often degraded by soft effects such as lens flare, haze, shadows, and reflections, which reduce aesthetics even though the underl

tutorialsarxiv-cs-cv

A Differentiable Framework for Global Circulation Model Precipitation Bias Correction

arXiv:2604.23045v1 Announce Type: new Abstract: Systematic biases in Global Circulation Model (GCM) outputs limit their direct applicability in regional planning, necessitating bias correction. Correc

safetyarxiv-cs-lg

Hardware

Agentic Fusion of Large Atomic and Language Models to Accelerate Materials Discovery

arXiv:2604.23758v1 Announce Type: new Abstract: The discovery of novel materials is critical for global energy and quantum technology transitions. While deep learning has fundamentally reshaped this l

hardwarearxiv-cs-lg

Tutorials

Cross-Course Generalizability of SRL-Aligned Predictive Models Using Digital Learning Traces

arXiv:2604.22812v1 Announce Type: cross Abstract: STEM dropout rates remain high at universities, particularly in computer science programs with theory-intensive courses. Digital learning environments

tutorialsarxiv-cs-lg

DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining

arXiv:2604.23054v1 Announce Type: cross Abstract: Predicting the outcomes of prospective clinical trials remains a major challenge for large language models. Prior work has shown that both traditional

Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learning

model-releasesarxiv-cs-cv

arXiv:2507.14137v4 Announce Type: replace Abstract: We present Franca (pronounced Fran-ka): free one; the first fully open-source (data, code, weights) vision foundation model that matches and in many

How Sensitive Are Safety Benchmarks to Judge Configuration Choices?

model-releasesarxiv-cs-cl

arXiv:2604.24074v1 Announce Type: new Abstract: Safety benchmarks such as HarmBench rely on LLM judges to classify model responses as harmful or safe, yet the judge configuration, namely the combinati

Human-1 by Josh Talks: A Full-Duplex Conversational Modeling Framework in Hindi using Real-World Conversations

arXiv:2604.23295v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems can model natural conversational behaviours such as interruptions, overlaps, and backchannels, yet such systems re

applicationsarxiv-cs-ai

Large language model-enabled automated data extraction for concrete materials informatics

arXiv:2604.22938v1 Announce Type: cross Abstract: The promise of data-driven materials discovery remains constrained by the scarcity of large, high-quality, and accessible experimental datasets. Here,

Learning to Rotate: Temporal and Semantic Rotary Encoding for Sequential Modeling

arXiv:2604.24717v1 Announce Type: new Abstract: Every Transformer architecture dedicates enormous capacity to learning rich representations in semantic embedding space -- yet the rotation manifold act

applicationsarxiv-cs-ai

LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models

arXiv:2604.23809v1 Announce Type: new Abstract: Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity s

applicationsarxiv-cs-cl

Meta-Ensemble Learning with Diverse Data Splits for Improved Respiratory Sound Classification

arXiv:2604.24096v1 Announce Type: cross Abstract: Training reliable respiratory sound classification models remains challenging due to the limited size and subject diversity of datasets. Ensemble meth

Hardware

Non-Destructive Prediction of Fruit Ripeness and Firmness Using Hyperspectral Imaging and Lightweight Machine Learning Models

arXiv:2604.22788v1 Announce Type: cross Abstract: Post-harvest fruit quality assessment is essential for reducing food waste, yet reliable non-destructive methods typically depend on expensive hypersp

hardwarearxiv-cs-lg

Agents

PhysNote: Self-Knowledge Notes for Evolvable Physical Reasoning in Vision-Language Model

arXiv:2604.24443v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated strong performance on textbook-style physics problems, yet they frequently fail when confronted with dyn

agentsarxiv-cs-ai

Local Ai

S^2IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction

arXiv:2604.23296v1 Announce Type: cross Abstract: Aspect Sentiment Quad Prediction (ASQP) has seen significant advancements, largely driven by the powerful semantic understanding and generative capabi

local-aiarxiv-cs-ai

Hardware

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models

arXiv:2604.24708v1 Announce Type: cross Abstract: Training large neural networks with data-parallel stochastic gradient descent allocates N GPU replicas to compute effectively identical updates -- a p

hardwarearxiv-cs-ai

SWE-QA: Can Language Models Answer Repository-level Code Questions?

model-releasesarxiv-cs-cl

arXiv:2509.14635v2 Announce Type: replace Abstract: Understanding and reasoning about entire software repositories is an essential capability for intelligent software engineering tools. While existing

Zero-shot Large Language Models for Automatic Readability Assessment

arXiv:2604.24470v1 Announce Type: new Abstract: Unsupervised automatic readability assessment (ARA) methods have important practical and research applications (e.g., ensuring medical or educational ma

Agents

AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model Selection

arXiv:2602.11931v2 Announce Type: replace-cross Abstract: Evolutionary agentic systems intensify the trade-off between computational efficiency and reasoning capability by repeatedly invoking large la

agentsarxiv-cs-ai

AromaGen: Interactive Generation of Rich Olfactory Experiences with Multimodal Language Models

arXiv:2604.01650v2 Announce Type: replace-cross Abstract: Smell's deep connection with food, memory, and social experience has long motivated researchers to bring olfaction into interactive systems. Y

Local Ai

GenMatter: Perceiving Physical Objects with Generative Matter Models

arXiv:2604.22160v1 Announce Type: cross Abstract: Human visual perception offers valuable insights for understanding computational principles of motion-based scene interpretation. Humans robustly dete

local-aiarxiv-cs-ai

HubRouter: A Pluggable Sub-Quadratic Routing Primitive for Hybrid Sequence Models

model-releasesarxiv-cs-lg

arXiv:2604.22442v1 Announce Type: new Abstract: We introduce HubRouter, a pluggable module that replaces O(n^2) attention layers with O(nM) hub-mediated routing, where M =20 shows increasing seed sens

Sharpness-Aware Poisoning: Enhancing Transferability of Injective Attacks on Recommender Systems

arXiv:2604.22170v1 Announce Type: new Abstract: Recommender Systems~(RS) have been shown to be vulnerable to injective attacks, where attackers inject limited fake user profiles to promote the exposur

applicationsarxiv-cs-lg

A Scale-Adaptive Framework for Joint Spatiotemporal Super-Resolution with Diffusion Models

arXiv:2604.21903v1 Announce Type: cross Abstract: Deep-learning video super-resolution has progressed rapidly, but climate applications typically super-resolve (increase resolution) either space or ti

24 Apr 2026

ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Response