Search: “models”

Feature Interaction Modeling for Physics-Informed Neural Networks and Neural Operators

arXiv:2607.28762v1 Announce Type: new Abstract: This work embeds feature interaction modules derived from factorization machines (FMs) into physics-informed neural networks (PINNs) and neural operator

3 Aug 2026

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FibVLA: An Efficient Temporal Vision-Language-Action Model with Fibonacci Sampling

DGX agent

arXiv:2607.29596v1 Announce Type: cross Abstract: Vision-language-action models (VLAs), which leverage the cognition of multimodal information to infer physical-world actions, provide a generalized so

applicationsarxiv-cs-cv

3 Aug 2026

Mitigating Class-Tail Undercoverage in Medical Vision-Language Models under Clinical Shift

arXiv:2607.28696v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) can retain high observed marginal coverage after clinical shift while substantially under-covering an individual

local-aiarxiv-cs-cv

3 Aug 2026

Behavioral Controllability of Agentic Models for Information Extraction: From Fixed Workflows to Reflective Agents

arXiv:2607.15715v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used for complex information-extraction tasks, yet it remains unclear whether agentic components

agentsarxiv-cs-ai

Tutorials

Can Large Language Models Execute Parent Orders?

arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution

tutorialsarxiv-cs-cl

Applications

Cocktail-Talker: Multi-Speaker Dialog Modeling in Noisy Social Environments with Turn Action GRPO

arXiv:2607.27756v1 Announce Type: cross Abstract: Spoken dialog systems are typically designed for clean, dyadic interactions in which a single user and an assistant take turns speaking. Real-world so

applicationsarxiv-cs-cl

Cybersecurity Detection Classification with Reasoning-enabled Language Models

arXiv:2607.28460v1 Announce Type: new Abstract: A major issue in Security Operations Centers (SOCs) is alert fatigue, as the number of detections reported is more than staff can triage in a given day.

Failure Detection for Surgical Robot Imitation Policies via Flow-Matching World Modeling

arXiv:2607.27511v1 Announce Type: new Abstract: Imitation learning has shown increasing promise for autonomous robotic surgery, yet safe deployment remains challenging due to the safety-critical natur

safetyarxiv-cs-ro

GLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation

arXiv:2607.28397v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) over knowledge graphs requires retrievers that can effectively capture both graph structure and semantic informat

Latent States in Neural Networks: Recovering the Temporal Structure of Drifting Data from Model Weights

arXiv:2607.27482v1 Announce Type: cross Abstract: A temporally drifting data stream may pass through discrete regimes rather than changing continuously. We ask whether such regimes are recoverable fro

A Closer Look at Dynamic Scene Graph Generation In the Era of Multimodal Large Language Models

arXiv:2503.15846v2 Announce Type: replace Abstract: Dynamic Scene Graph Generation (DSGG) aims to capture objects and their evolving relations in videos. Despite recent progress, the practicality and

AtmosERC: Modeling Dialogue-Level Affective Atmosphere for Emotion Recognition in Conversation

arXiv:2607.26726v1 Announce Type: new Abstract: Emotion Recognition in Conversation (ERC) aims to predict utterance-level emotions in dialogues and has largely advanced through context-centric modelin

Global Exponential Stabilization of the Kinematic Bicycle Model of a Car in Polar Coordinates

arXiv:2607.26442v1 Announce Type: cross Abstract: At parking speeds, the kinematic bicycle is the prevailing model for car-like vehicles. Yet, despite its wide use, stabilizing feedback laws for this

researcharxiv-cs-ro

Harnessing Large Language Models for Intelligent Resource Allocation in the Internet of Everything

arXiv:2607.26602v1 Announce Type: cross Abstract: The rapid development of the Internet of Everything (IoE) is accelerating the adoption of intelligent applications. However, the massive number of con

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities

arXiv:2505.01043v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t

RL^2-VLA: Adaptive RL Latent Compositional Steering with Test-Time Scaling for Vision-Language-Action Models

arXiv:2607.26991v1 Announce Type: new Abstract: Despite the impressive visuomotor capabilities enabled by Vision-Language-Action (VLA) models, their performance often degrades on challenging and out-o

safetyarxiv-cs-ro

SPROUT: A Scalable Diffusion Foundation Model for Agricultural Vision

arXiv:2603.27519v2 Announce Type: replace Abstract: Image-based plant phenotyping depends on dense structural understanding of crops, yet pixel-level annotation remains expensive across species, organ

Using large language models to probe the limits of atom-centered structural descriptors

arXiv:2607.26984v1 Announce Type: cross Abstract: Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modelin

Where Physics Meets Privacy: Federated PINNs for Privacy-Preserving Brain Tumor Biomechanical Modeling

arXiv:2607.26207v1 Announce Type: new Abstract: Brain tumors such as glioma, meningioma, and pituitary adenoma alter the mechanical behavior of soft brain tissue, yet common diagnostic methods rely on

local-aiarxiv-cs-cv

AGMark: Attention-Guided Dynamic Watermarking for Large Vision-Language Models

arXiv:2602.09611v2 Announce Type: replace-cross Abstract: Watermarking has emerged as a pivotal solution for content traceability and intellectual property protection in large vision language models (

Tutorials

Explicit Layer Modeling for Video Object Insertion and Layer Decomposition

arXiv:2607.25802v1 Announce Type: new Abstract: Most video editing systems still lack explicit layered video representations, limiting their ability to perform realistic compositing, object reuse, and

tutorialsarxiv-cs-cv

Exploring Line Bundle Standard Models with Transformers

arXiv:2607.00078v2 Announce Type: cross Abstract: We propose a Transformer-based Reinforcement Learning architecture, 'LB-Explorer', to search for heterotic line bundle standard models arising from co

Applications

Reading Without a Reader: Large Language Models Collapse Reading and Writing into a Single Entangled Code

arXiv:2607.24797v1 Announce Type: cross Abstract: In the literate human brain, reading and writing are two doubly-dissociable systems: a ventral decoding route (impaired in pure alexia) and a fronto-p

applicationsarxiv-cs-ai

SepPrune:A Separator-based Pruning Framework for Efficient Multimodal Large Language Models

arXiv:2607.25818v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs), such as Qwen2.5-VL and InternVL3, generate large numbers of vision tokens for high-resolution inputs, l

Specula: Scaling formal specifications for autonomous model checking of system code

arXiv:2607.25333v1 Announce Type: cross Abstract: Specula is a push-button agentic system that generates high-quality formal specifications for large, complex system code and uses the specifications f

agentsarxiv-cs-ai

An adaptive multi-fuzzy logic model for diagnosing transformer faults using dynamic weight optimization

arXiv:2607.23486v1 Announce Type: new Abstract: Dissolved gas analysis (DGA) is crucial for diagnosing early power transformer failures. Traditional DGA interpretation methods like Duval Triangle, IEC

Attention-Guided Layer Selection for Contrastive Decoding in Large Language Models

arXiv:2607.23067v1 Announce Type: cross Abstract: Contrastive decoding methods such as DoLa improve the factuality of Large Language Models (LLMs) by contrasting the output distributions of mature and

Comparing Optimization Models for Radiotherapy Scheduling

arXiv:2607.22539v1 Announce Type: cross Abstract: The Radiotherapy Scheduling Problem (RTSP) involves determining an optimal schedule for patients undergoing radiation treatments, a task that has a ma

Hardware

CSV-Decode: Certifiable Sub-Vocabulary Decoding for Efficient Large Language Model Inference

arXiv:2511.21702v2 Announce Type: replace-cross Abstract: Large language models face significant computational bottlenecks during inference due to the expensive output layer computation over large voc

hardwarearxiv-cs-ai

DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models

arXiv:2607.23944v1 Announce Type: new Abstract: Human visual reasoning typically follows a coarse-to-fine attention process, starting from global scene understanding and gradually focusing on question

Moral Hazard in Multi-Agent Language Models

arXiv:2607.23982v1 Announce Type: cross Abstract: Cooperation can fail when socially valuable effort is costly, weakly observable, and mainly benefits others. Drawing on Holmstrom's team moral-hazard

MS-GPT: Rethinking MS/MS De Novo Structure Elucidation as Spectrum-Induced Posterior Querying of a Molecule-Language Model

arXiv:2607.23607v1 Announce Type: cross Abstract: Molecular structure elucidation from tandem mass spectra (MS/MS) is a central inverse problem in analytical chemistry. Most existing approaches to MS/

safetyarxiv-cs-cl

Stress-testing large language model agents in a robotic chemistry laboratory

arXiv:2607.23045v1 Announce Type: new Abstract: AI is evaluated through knowledge, reasoning and plan generation, yet scientific agency requires reliable physical action and adaptation to evidence. He

agentsarxiv-cs-ai

Leveraging External Knowledge for Historical Document Restoration via Retrieval-Augmented Large Language Models

arXiv:2607.21936v1 Announce Type: new Abstract: Historical documents act as invaluable knowledge archives but often suffer from illegibility due to physical deterioration and damage. While existing re

local-aiarxiv-cs-cl

Reasoning Denoiser: Denoising Reasoning Traces for Hallucination Detection in Large Reasoning Models

arXiv:2607.22098v1 Announce Type: cross Abstract: Large reasoning models (LRMs) generate long reasoning traces before producing final answers. While these traces may contain useful signals for halluci

Rethinking Multi-Branch and Cross-Backbone Fusion for Vehicle Re-Identification in the Foundation-Model Era

arXiv:2607.22068v1 Announce Type: new Abstract: Multi-branch architectures and CNN-Transformer fusion have long been regarded as effective ways to improve vehicle re-identification (Re-ID) by combinin

Universal BCI Personalization: One API for Frozen EEG Trunks and Foundation Models

arXiv:2607.22397v1 Announce Type: cross Abstract: Frozen EEG encoders proliferate; per-model fine-tune defaults do not scale. We present Nimbus Personalizer: one contract encode to Bayesian head to Br

ViTacWorld: Scaling Visuo-Tactile World Models for Contact-Rich Robot Manipulation

arXiv:2607.22530v1 Announce Type: new Abstract: Contact-rich robot manipulation requires physical interaction cues that are often invisible to cameras, making tactile sensing essential for robust cont

safetyarxiv-cs-ro

Diagnosing Pathological Chain-of-Thought in Reasoning Models

arXiv:2602.13904v2 Announce Type: replace Abstract: Chain-of-thought (CoT) reasoning is fundamental to modern LLM architectures and represents a critical intervention point for AI safety. However, CoT

Tutorials

Equivariant Conditional Diffusion Model for Head and Neck CT Image Synthesis from CBCT

arXiv:2509.21913v2 Announce Type: replace-cross Abstract: Background: Cone-beam computed tomography CBCT is a commonly used modality for image guided radiotherapy. It offers real time anatomical visua

tutorialsarxiv-cs-ai

GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation

arXiv:2607.21036v1 Announce Type: new Abstract: Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic under

Human-in-the-Loop Large Language Model Framework for Identification of Cutaneous Immune-Related Adverse Events

arXiv:2607.20428v1 Announce Type: new Abstract: This study evaluated a retrieval-augmented, multi-agent large language model (LLM)-driven, human-in-the-loop framework for detecting cutaneous immune-re

agentsarxiv-cs-cl

Loss-Complexity Landscape and Model Structure Functions

arXiv:2507.13543v5 Announce Type: replace-cross Abstract: We develop a framework for dualizing the Kolmogorov structure function h_x(alpha), which then allows using computable complexity proxies. We e

Monkey King Bang: A Unified Scientific Multimodal Foundation Model

arXiv:2607.20557v1 Announce Type: cross Abstract: Scientific discovery is increasingly shifting from isolated disciplines to multi-domain reasoning, and AI for science faces a similar transition. Exis

Naju: A Native Discrete State-Space Model with Independent Retention and Writing for Long-Sequence Memory

arXiv:2607.21000v1 Announce Type: new Abstract: Long-sequence memory tracking places two opposing demands on a recurrent state: near-lossless retention of stored bindings over long horizons, and activ

local-aiarxiv-cs-ai

Non-Zipfian Distribution of Stopwords or Function Words and Subset Selection Models

arXiv:2603.04691v2 Announce Type: replace Abstract: Stopwords and function words are relatively less informative for the content of a language and more often play a structural role in a sentence. Stop

Physics-Informed Deep Learning Model for Cross-Modality Super-Resolution in Fluorescence Microscopy

arXiv:2607.21190v1 Announce Type: new Abstract: Cross-modality image translation offers a route to super-resolution fluorescence microscopy from low-resolution images while reducing phototoxicity and

Routing Subspaces: Auditing Evaluation-to-Deployment Mismatch in Fine-Tuned Language Models

arXiv:2607.20436v1 Announce Type: cross Abstract: Safety evaluations often assume that behavior observed during testing reflects behavior in ordinary use, but fine-tuning can break this assumption. A