Search: “model-releases”

DART: Distillation-Aware Reparameterization for Training-Free LoRA Reuse in Few-Step Video Diffusion Models

arXiv:2609.20051v1 Announce Type: new Abstract: Step distillation reduces the cost of video generation, but reusing a LoRA trained for a longer trajectory can alter its functional effect or degrade ta

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

DGX agent

arXiv:2609.19969v1 Announce Type: new Abstract: The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost

model-releasesarxiv-cs-cl

18 Sept 2026

DeltaSelect: Affordable A/B Testing for Coding Agents

arXiv:2609.19607v1 Announce Type: cross Abstract: Coding-agent benchmarks are built for broad and comprehensive comparisons, not frequent development decisions. Individual runs vary, full suites are e

Design of the IBM Granite 5.0 TurboCTC ASR Model

arXiv:2609.20104v1 Announce Type: new Abstract: We describe the architecture, training methodology and inference speedups of Granite 5.0 Turbo CTC, a 470 million parameter encoder-only model with an e

Dictionary-Constrained Grapheme-to-Phoneme for Unsegmented Languages from LLM-Annotated Data

arXiv:2609.19805v1 Announce Type: new Abstract: Grapheme-to-phoneme (G2P) conversion turns raw text into its phonemic form and is an essential part of both text-to-speech (TTS) and automatic speech re

Digital Twins for Opinion Dynamics: A Generative LLM Framework for Social Networks

arXiv:2609.19913v1 Announce Type: new Abstract: The study of opinion dynamics in social networks is one of the key challenges in computational social science with direct relevance to understanding pol

DocAttriBench: Benchmarking Answer Grounding in Document Visual Question Answering

arXiv:2609.20574v1 Announce Type: new Abstract: Answer grounding in document visual question answering remains an open challenge: most benchmarks lack grounding annotations or provide limited-quality

Drag-Aware Aerodynamic Manipulability for Torque-Limited Redundant Multirotors: Aerodynamic Promptness based on the Symmetric Acceleration Capacity

arXiv:2603.07998v2 Announce Type: replace-cross Abstract: Aerodynamic promptness quantifies how rotor-speed variations generate multirotor wrench variations, but its Euclidean formulation assigns the

Dynamic-LIVO: A Dynamic-Aware LiDAR-Inertial-Visual Odometry System Using Spatio-Temporal Normals

model-releasesarxiv-cs-ro

arXiv:2609.19336v1 Announce Type: new Abstract: This paper proposes Dynamic-LIVO, a dynamic-aware LiDAR-Inertial-Visual Odometry (LIVO) system for robust state estimation and static colored mapping in

Effective and Efficient Threat Hunting with Small Language Models

arXiv:2512.06660v3 Announce Type: replace-cross Abstract: Analysts in Security Operations Centers query massive telemetry streams using Kusto Query Language (KQL), but writing correct KQL demands spec

Elastic Spectral State Space Models for Train-Once Budgeted Inference

arXiv:2601.22488v3 Announce Type: replace Abstract: Modern sequence models are typically trained at a fixed computational capacity, while real-world applications require deployment across platforms wi

EmbodiedMind: Adaptive Data Curation and Prefix-Tree Reinforcement Learning for Efficient Embodied Intelligence

arXiv:2609.19659v1 Announce Type: cross Abstract: Training embodied foundation models typically requires massive-scale datasets and extensive computational resources, yet often suffers from three crit

Enhanced Agriculture-informed Neural Network by Domain Knowledge

arXiv:2609.19466v1 Announce Type: new Abstract: Accurate prediction of nitrous oxide (N2O) emissions from agriculture is important for assessing environmental impacts and supporting sustainable farmin

Epidemiological Causal Graph Identification: Challenges, Identifiability and Algorithms

arXiv:2609.20676v1 Announce Type: new Abstract: Causal discovery from observational data is fundamental to statistics and machine learning, yet determining causal direction without interventions neces

Equivariant Filter Design for Acoustic and Depth Aided Inertial Navigation Systems

model-releasesarxiv-cs-ro

arXiv:2609.19742v1 Announce Type: new Abstract: Autonomous Underwater Vehicles (AUVs) navigating without GPS typically fuse inertial measurements with acoustic Doppler Velocity Log (DVL) velocities an

ERCPMP-Gx: Endoscopic Image and Video Dataset for Morphological, Histopathological, and Genomic Characterization of Colorectal Polyposis

arXiv:2609.20815v1 Announce Type: cross Abstract: Hereditary polyposis syndromes can be precursor lesions to colorectal cancer and are associated with a broad spectrum of extracolonic tumors. Early id

Evaluating Communicative Success in Machine-Translated Conversation

arXiv:2609.19885v1 Announce Type: new Abstract: Interpreter agents built on machine translation (MT) increasingly mediate live conversation between people who do not share a language, yet we still eva

Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark

arXiv:2508.06734v3 Announce Type: replace-cross Abstract: While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when

Exploring Sparsity and Smoothness of Arbitrary Lp Norms in Adversarial Attacks

arXiv:2602.06578v2 Announce Type: replace-cross Abstract: Adversarial attacks against deep neural networks are commonly constructed under ell_p norm constraints, most often using p=1, p=2 or p=infty,

F^{2}DR: A Fine-Grained Full-Pipeline Reward Framework for DeepSearch Workflows

arXiv:2609.19827v1 Announce Type: new Abstract: With the widespread industrial deployment of Large Language Models (LLMs), DeepSearch has emerged as the dominant paradigm for resolving complex user qu

FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System

arXiv:2609.20175v1 Announce Type: cross Abstract: The filter bubble is a notorious issue in Recommender Systems (RSs), which describes the phenomenon whereby users are exposed to a limited and narrow

Fast Preemptive Robustification: High-Frequency Response Anti-Aligns Shared Vulnerability

arXiv:2603.25244v2 Announce Type: replace Abstract: Adversarial attacks can readily compromise deep neural networks (DNNs). In particular, transferable attacks (TAs) exploit the shared vulnerabilities

FCA-Guided Counterfactual Explanations for Multi-Modal Breast Cancer Diagnosis: A Framework Achieving Perfect Validity with Emergent Sparsity

arXiv:2609.20067v1 Announce Type: new Abstract: Deep learning models for multi-modal breast cancer diagnosis achieve high predictive accuracy but remain clinically unacceptable without actionable, cou

FedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction

arXiv:2609.20026v1 Announce Type: new Abstract: Urban traffic forecasting often relies on information distributed across stakeholders who may be unable to share raw data due to privacy or commercial c

FedFIbOS: Fisher Importance based Optimal Submodelling for Heterogeneous Federated Learning

arXiv:2609.19559v1 Announce Type: new Abstract: Heterogeneous federated learning requires clients with diverse computational capacities to collaboratively train a global model, where each client train

FedVideoMAE: Efficient Federated Video Moderation with Differential Privacy and Secure Aggregation

arXiv:2512.18809v3 Announce Type: replace-cross Abstract: Short-form video moderation is increasingly pushed toward edge and privacy-sensitive settings, where users may intend videos for a limited aud

Fine-Tuning Models for Biomedical Relation Extraction

arXiv:2609.20169v1 Announce Type: new Abstract: Next-Generation Sequencing has revolutionized the study of genetic mutations, enabling large-scale investigations into their roles in disease developmen

Fingerprinting Multimodal Large Language Models

arXiv:2609.20457v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) enable a wide range of image-text reasoning tasks, recent incidents indicate that they are vulnerable t

FINSKILLOPS: A Self-Evolving Multi-Agent System for SEC Filing QA

arXiv:2609.19680v1 Announce Type: new Abstract: Financial QA systems are typically improved before deployment through better retrieval, prompting, or agent coordination, leaving their reliability beha

Form Over Content In Gradient-Based Data Attribution Methods

arXiv:2609.19589v1 Announce Type: cross Abstract: Data attribution methods using gradient similarity are widely used to analyze and select training data for large language models, but what gradient si

FreqDINO++: A Frequency-Guided Multi-Task Routing Vision Foundation Model for Universal Ultrasound Analysis

arXiv:2609.20340v1 Announce Type: new Abstract: Ultrasound image analysis plays a crucial role in cancer screening and prenatal diagnosis, yet comprehensive assessment requires jointly addressing task

From Intent to Action: Benchmarking LLM Safety in Vehicle Voice Command Authorization

arXiv:2609.19630v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into vehicle voice assistants. But linking natural-language requests to vehicle functions creat

From Parameters to Behaviors: A Survey of Model Fusion for Large Language Models

arXiv:2609.19553v1 Announce Type: new Abstract: Model fusion integrates the capabilities from source models into a single target model. As of June 2026, Hugging Face hosts more than 2M models. This gr

GAPrompt++: Multi-Granular Geometry-Aware Point Cloud Prompt for 3D Vision Model

arXiv:2609.19716v1 Announce Type: new Abstract: Pre-trained 3D vision models have substantially advanced point cloud analysis, yet adapting them to downstream tasks via full fine-tuning is computation

Geopolitical Divisions Across Languages in Large Language Models

arXiv:2609.20005v1 Announce Type: new Abstract: People increasingly turn to AI chatbots for news and explanations of world events. But do they receive the same political answers when they ask in diffe

Grounded Product Understanding in Livestream Videos

arXiv:2609.20508v1 Announce Type: new Abstract: E-commerce livestreams have emerged as an important channel for presenting products to online consumers, containing multiple products whose information

Guideline-grounded retrieval-augmented generation for ophthalmic clinical decision support

arXiv:2603.21925v2 Announce Type: replace Abstract: In this work, we propose Oph-Guid-RAG, a multimodal visual RAG system for ophthalmology clinical question answering and decision support. We treat e

Harm Laundering in GPT Models: Evidence That Gender Discrimination Is Transformed Rather Than Reduced Across Safety-Trained Generations

arXiv:2609.20779v1 Announce Type: cross Abstract: Safety evaluations for large language models rely on surface-form classifiers that report declining harm scores across model generations. We provide e

How to Guide Your Language Flow

arXiv:2609.19356v1 Announce Type: cross Abstract: We introduce a new method to guide flow matching models. Our approach, which we call probe guidance, uses the frozen internal states of an existing di

HyperAMS-Net: Adaptive Multi-Scale Spatial Hypergraph Network for Brain Disorder Classification

arXiv:2609.19755v1 Announce Type: cross Abstract: Accurate classification of brain disorders from neuroimaging data remains challenging because of substantial inter-subject heterogeneity and the compl

Interpretable and Calibrated Classification of Clinical Data Using Supervised Feature Binarization

arXiv:2607.15394v2 Announce Type: replace Abstract: Black-box models limit the adoption of artificial intelligence in medicine because their predictions are difficult to interpret and reproduce. We pr

Intrinsic Sequence-Likelihood Confidence in Retrieval-Dominated Extractive QA: Two Pre-Specified Negatives, and What They Do and Do Not Attribute

arXiv:2609.19942v1 Announce Type: new Abstract: In extractive document question answering whose questions were generated from the passages that contain their answers -- so that retrieval recovers 92-9

Is It Still Worth Training a Classical Model in the Era of LLMs? A Crossover Benchmark on Tabular Data

arXiv:2609.20218v1 Announce Type: cross Abstract: Large language models can label a tabular row from a plain-English description with no training - a capability now shipping in mainstream spreadsheet

JEPA-WAM: Connecting Generated Visual Instructions to World Action Models through JEPA Latent Representations

arXiv:2609.20277v1 Announce Type: new Abstract: World Action Models (WAMs) have demonstrated strong robotic manipulation capabilities by augmenting pretrained video generative models with action exper

KoNeoBench: A Curated Evaluation Dataset for LLM Understanding of Korean Neologisms

arXiv:2609.19916v1 Announce Type: cross Abstract: Large language models (LLMs) are typically evaluated on static benchmarks, even though natural language constantly evolves through newly emerging word

KoUniTalk: A Lightweight Articulation-Centered Korean-English 3D Talking Face Benchmark

arXiv:2609.19840v1 Announce Type: new Abstract: High-quality 3D talking face datasets remain largely English- centric, and Korean 3D facial motion data are difficult to combine with standard English b

Layer-wise Curriculum Learning for Efficient LLM Compression

arXiv:2609.19213v1 Announce Type: cross Abstract: In this paper, we introduce layer-wise curriculum learning for efficient LLM compression. The proposed method facilitates the knowledge transfer from

Learning-Based Reconstruction of Optical Properties in Bilayered Media from Single-distance Time-Resolved Reflectance Measurements

arXiv:2609.19786v1 Announce Type: new Abstract: The inverse problem of reconstructing optical properties, specifically absorption and scattering coefficients, in layered biological media from time-dom