Search: “models”

DARE: Diffusion Language Model Activation Reuse for Efficient Inference

arXiv:2605.08134v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to auto-regressive (AR) models, offering greater expressive capacity a

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Dystruct: Dynamically Structured Diffusion Language Model Decoding via Bayesian Inference

DGX agent

arXiv:2605.09820v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as a promising alternative to autoregressive models, primarily due to their ability to enable par

local-aiarxiv-cs-lg

12 May 2026

Local Ai

FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference

arXiv:2605.08760v1 Announce Type: new Abstract: Federated Learning (FL) facilitates collaborative model training across decentralized clients while preserving data privacy by avoiding raw data exchang

local-aiarxiv-cs-lg

LLiMba: Sardinian on a Single GPU -- Adapting a 3B Language Model to a Vanishing Romance Language

arXiv:2605.09015v1 Announce Type: new Abstract: Sardinian, a Romance language with roughly one million speakers, has minimal presence in modern NLP. Commercial services do not support it, and current

Meow-Omni 1: A Multimodal Large Language Model for Feline Ethology

arXiv:2605.09152v1 Announce Type: new Abstract: Deciphering animal intent is a fundamental challenge in computational ethology, largely because of semantic aliasing, the phenomenon where identical ext

SLayerGen: a Crystal Generative Model for all Space and Layer Groups

arXiv:2605.08262v1 Announce Type: cross Abstract: Crystal generative models have shown rapid progress for accelerating the discovery of bulk, periodic materials. However, many material systems such as

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training

arXiv:2605.08738v1 Announce Type: cross Abstract: Structured pruning and knowledge distillation (KD) are typical techniques for compressing large language models, but it remains unclear how they shoul

Towards a Large Language-Vision Question Answering Model for MSTAR Automatic Target Recognition

arXiv:2605.10772v1 Announce Type: cross Abstract: Large language-vision models (LLVM), such as OpenAI's ChatGPT and GPT-4, have gained prominence as powerful tools for analyzing text and imagery. The

Towards Compact Sign Language Translation: Frame Rate and Model Size Trade-offs

arXiv:2605.09554v1 Announce Type: new Abstract: Sign Language Translation (SLT) converts sign language videos into spoken-language text, bridging communication between Deaf and hearing communities. Cu

Uncovering Intra-expert Activation Sparsity for Efficient Mixture-of-Expert Model Execution

arXiv:2605.08575v1 Announce Type: cross Abstract: Mixture of Experts (MoE) architecture has become the standard for state-of-the-art large language models, owing to its computational efficiency throug

Amortized Multi-Objective Optimization Across Tasks with Generative Solution Modeling

arXiv:2511.09598v5 Announce Type: replace Abstract: Many real-world applications require solving families of expensive multi-objective optimization problems~(EMOPs) under varying operational condition

BGM-IV: an AI-powered Bayesian generative modeling approach for instrumental variable analysis

arXiv:2605.07029v1 Announce Type: cross Abstract: Instrumental-variable (IV) regression enables causal estimation under endogeneity, but modern IV problems often involve nonlinear structural effects a

DT-PBO: an Interpretable Tree-based Surrogate Model for Preferential Bayesian Optimization

arXiv:2512.14263v2 Announce Type: replace-cross Abstract: Preferential Bayesian Optimization (PBO) aims to find a decision-maker's most preferred solution in as few pairwise comparisons as possible. E

Frequency-Aware Model Parameter Explorer: A new attribution method for improving explainability

arXiv:2510.03245v2 Announce Type: replace-cross Abstract: State-of-the-art attribution methods rely on adversarial sample generation that applies an all-pass filter across the frequency spectrum, disc

MicroBi-ConvLSTM: An Ultra-Lightweight Efficient Model for Human Activity Recognition on Resource Constrained Devices

model-releasesarxiv-cs-cv

arXiv:2602.06523v2 Announce Type: replace Abstract: Human Activity Recognition (HAR) on resource constrained wearables requires models that balance accuracy against strict memory and computational bud

Outlier Smoothing with Closed-Form Rotations for W4A4 Large Language Model Quantization

arXiv:2511.22316v2 Announce Type: replace Abstract: Large Language Models (LLMs) quantization facilitates deploying LLMs in resource-limited settings, but existing methods that combine incompatible gr

Stabilized neural Hamilton--Jacobi--Bellman solvers: Error analysis and applications in model-based reinforcement learning

arXiv:2605.07116v1 Announce Type: cross Abstract: Physics-informed neural solvers offer a promising route to model-based reinforcement learning in continuous time, where optimal feedback synthesis is

safetyarxiv-cs-ai

TajPersLexon: A Tajik-Persian Lexical Resource and Hybrid Model for Cross-Script Low-Resource NLP

arXiv:2605.06886v1 Announce Type: new Abstract: This work introduces TajPersLexon, a curated Tajik--Persian parallel lexical resource of 40,112 word and short-phrase pairs for cross-script lexical ret

A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers

arXiv:2605.03391v1 Announce Type: cross Abstract: Weighted first-order model counting (WFOMC) is a central task in lifted probabilistic inference: It asks for the weighted sum of all models of a first

Agent-Based Modeling of Low-Emission Fertilizer Adoption for Dairy Farm Decarbonisation using Empirical Farm Data

arXiv:2605.03648v1 Announce Type: new Abstract: To understand complex system dynamics in dairy farming, it is essential to use modeling tools that capture farm heterogeneity, social interactions, and

safetyarxiv-cs-ai

Cross-Tokenizer Likelihood Scoring Algorithms for Language Model Distillation

arXiv:2512.14954v2 Announce Type: replace Abstract: Computing next-token likelihood ratios between two language models (LMs) is a standard task in training paradigms such as knowledge distillation. Si

Hardware

Deep Wave Network for Modeling Multi-Scale Physical Dynamics

arXiv:2605.04198v1 Announce Type: new Abstract: Performance of deep learning models is strongly governed by architectural capacity, with width and depth as primary controls. However, in physical-scien

hardwarearxiv-cs-lg

Lookahead Drifting Model

arXiv:2605.04060v1 Announce Type: cross Abstract: Recently, a new paradigm named drifting model has been proposed for mapping distributions, which achieves the SOTA image generation performance over I

researcharxiv-cs-cv

Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking

arXiv:2605.04607v1 Announce Type: new Abstract: This paper presents a multi-phase whole-body model predictive control approach for bipedal walking, combining a detailed whole-body model in the near ho

researcharxiv-cs-ro

TCM-Serve: Modality-aware Scheduling for Multimodal Large Language Model Inference

arXiv:2603.26498v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) power platforms like ChatGPT, Gemini, and Copilot, enabling richer interactions with text, images, an

Local Ai

A Few-Step Generative Model on Cumulative Flow Maps

arXiv:2605.03623v1 Announce Type: new Abstract: We propose a unified, few-step generative modeling framework based on cumulative flow maps for long-range transport in probability space, inspired by fl

local-aiarxiv-cs-lg

A Unified Framework for Tabular Generative Modeling: Loss Functions, Benchmarks, and Improved Multi-objective Bayesian Optimization Approaches

arXiv:2405.16971v2 Announce Type: replace Abstract: Deep learning (DL) models require extensive data to achieve strong performance and generalization. Deep generative models (DGMs) offer a solution by

applicationsarxiv-cs-lg

Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling

arXiv:2507.07982v2 Announce Type: replace Abstract: Videos inherently represent 2D projections of a dynamic 3D world. However, our analysis suggests that video diffusion models trained solely on raw v

safetyarxiv-cs-cv

Tutorials

SCPRM: A Schema-aware Cumulative Process Reward Model for Knowledge Graph Question Answering

arXiv:2605.02819v1 Announce Type: new Abstract: Large language models excel at complex reasoning, yet evaluating their intermediate steps remains challenging. Although process reward models provide st

tutorialsarxiv-cs-ai

Counting as a minimal probe of language model reliability

arXiv:2605.02028v1 Announce Type: new Abstract: Large language models perform strongly on benchmarks in mathematical reasoning, coding and document analysis, suggesting a broad ability to follow instr

Tutorials

GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items

arXiv:2603.14259v2 Announce Type: replace-cross Abstract: Generative recommendation (GR) has shown strong potential for sequential recommendation in an end-to-end generation paradigm. However, existin

tutorialsarxiv-cs-ai

Shadow-Loom: Causal Reasoning over Graphical World Model of Narratives

arXiv:2605.02475v1 Announce Type: cross Abstract: Stories hold a reader's attention because they have causes, secrets, and consequences. Shadow-Loom is an experimental open-source framework that turns

SlimDiffSR: Toward Lightweight and Efficient Remote Sensing Image Super-Resolution via Diffusion Model Distillation

arXiv:2605.02198v1 Announce Type: new Abstract: Diffusion models have recently achieved remarkable performance in image super-resolution (SR), but their high computational cost limits practical deploy

applicationsarxiv-cs-cv

Being-H0.7: A Latent World-Action Model from Egocentric Videos

arXiv:2605.00078v1 Announce Type: cross Abstract: Visual-Language-Action models (VLAs) have advanced generalist robot control by mapping multimodal observations and language instructions directly to a

applicationsarxiv-cs-cv

Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe

arXiv:2605.00607v1 Announce Type: new Abstract: Probing is widely used to study which features can be decoded from language model representations. However, the common decoding probe approach has two l

Differentiable Autoencoding Neural Operator for Interpretable and Integrable Latent Space Modeling

arXiv:2510.00233v2 Announce Type: replace Abstract: Scientific machine learning has enabled the extraction of physical insights and data-driven modeling of high-dimensional spatiotemporal data, yet ac

LandSegmenter: Towards a Flexible Foundation Model for Land Use and Land Cover Mapping

arXiv:2511.08156v2 Announce Type: replace Abstract: Land Use and Land Cover (LULC) mapping is a fundamental task in Earth Observation (EO). However, current LULC models are typically developed for a s

researcharxiv-cs-cv

Lightweight Domain Adaptation of a Large Language Model for Legal Assistance in the Indian Context

arXiv:2505.22003v2 Announce Type: replace Abstract: In India, access to legal assistance for the general public has been observed to have a critical gap, as many citizens are not able to take full adv

LLM DNA: Tracing Model Evolution via Functional Representations

arXiv:2509.24496v3 Announce Type: replace Abstract: The explosive growth of large language models (LLMs) has created a vast but opaque landscape: millions of models exist, yet their evolutionary relat

researcharxiv-cs-lg

AutoSurfer -- Teaching Web Agents through Comprehensive Surfing, Learning, and Modeling

arXiv:2604.27253v1 Announce Type: new Abstract: Recent advances in multimodal large language models (LLMs) have revolutionized web agents that can automate complex tasks on websites. However, their ac

JaiTTS: A Thai Voice Cloning Model

arXiv:2604.27607v1 Announce Type: new Abstract: We present JaiTTS-v1.0, a state-of-the-art Thai voice cloning text-to-speech model built through continual training on a large Thai-centric speech corpu

applicationsarxiv-cs-cl

LLM-Guided Runtime Parameter Optimization for Energy-Efficient Model Inference

arXiv:2604.27032v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become an integral part of many real-world workflows. However, LLMs consume a lot of energy, which becomes a large c

Test-Time Distillation for Continual Model Adaptation

arXiv:2506.02671v3 Announce Type: replace Abstract: Deep neural networks often suffer performance degradation upon deployment due to distribution shifts. Continual Test-Time Adaptation (CTTA) aims to

safetyarxiv-cs-cv

Risk Reporting for Developers' Internal AI Model Use

arXiv:2604.24966v1 Announce Type: cross Abstract: Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a p

safetyarxiv-cs-ai

30 Apr 2026

Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

arXiv:2604.26694v1 Announce Type: cross Abstract: We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruc

30 Apr 2026

Interpretable Fuzzy Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts

arXiv:2604.24765v1 Announce Type: cross Abstract: P300-based brain-computer interfaces (BCIs) are widely used for communication, but population heterogeneity may alter the neural patterns available fo

29 Apr 2026

Modeling Human-Like Color Naming Behavior in Context

arXiv:2604.25674v1 Announce Type: new Abstract: Modeling the emergence of human-like lexicons in computational systems has advanced through the use of interacting neural agents, which simulate both le

29 Apr 2026

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters