Search: “models”

Mapping the City Through the Lens of Language Models

arXiv:2608.02971v1 Announce Type: new Abstract: Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and

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Noise-Aware Shrinkage for Differentially Private Zeroth-Order Fine-Tuning of Large Language Models

DGX agent

arXiv:2608.03277v1 Announce Type: new Abstract: Differentially private zeroth-order optimization (DP-ZO) enables memory-efficient private fine-tuning of large language models using only forward evalua

researcharxiv-cs-lg

5 Aug 2026

Speculative Correction: Draft-then-Refine Decoding for Diffusion Language Models

arXiv:2608.02625v1 Announce Type: cross Abstract: Diffusion language models (DLMs) can revise tokens bidirectionally, but standard decoding procedures often adapt them to left-to-right generation by p

local-aiarxiv-cs-ai

T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models

arXiv:2512.23953v2 Announce Type: replace Abstract: The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent video

Where Knowledge Collides: A Mechanistic Study of Intra-Memory Knowledge Conflict in Language Models

arXiv:2601.09445v2 Announce Type: replace-cross Abstract: In language models (LMs), intra-memory knowledge conflict arises when inconsistent information about the same subject is encoded within the mo

applicationsarxiv-cs-ai

Development and Validation of a Dynamic Kidney Failure Prediction Model based on Deep Learning: A Real-World Study with External Validation

arXiv:2501.16388v3 Announce Type: replace Abstract: Background: Chronic kidney disease (CKD), a progressive disease with high morbidity and mortality, has become a significant global public health pro

applicationsarxiv-cs-lg

Douyin Multimodal Embedding Model Technical Report

arXiv:2608.02148v1 Announce Type: cross Abstract: Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search

applicationsarxiv-cs-cl

Faster-WAM: Do World Action Models Need Deep Action Modules?

arXiv:2608.02365v1 Announce Type: cross Abstract: World Action Models (WAMs) couple robot action prediction with video world models. Existing WAMs with shared-backbone and Mixture-of-Transformers desi

researcharxiv-cs-lg

Few-Shot Biomedical Relation Extraction with Large Language Models: A Viable Alternative to Supervised Learning?

arXiv:2606.15412v2 Announce Type: replace Abstract: Biomedical relation extraction (BioRE) is a key step in transforming biomedical literature into structured knowledge. Most existing approaches rely

Isotonic Bradley-Terry Model for Paired Comparison Data

arXiv:2608.02081v1 Announce Type: new Abstract: In this paper, we study prediction problems for paired comparison data, for example, predicting the win probability between two unmatched players and ra

tutorialsarxiv-cs-lg

Orchestrating Dual-Boundaries: An Arithmetic Intensity Inspired Acceleration Framework for Diffusion Language Models

arXiv:2511.21759v2 Announce Type: replace Abstract: Diffusion-based large language models (dLLMs) have recently gained significant attention for their exceptional performance and inherent potential fo

PlantRig - From Bones to Branches: Adaptation of Autoregressive Rigging Models for Plant Skeletal Reconstruction

arXiv:2608.01072v1 Announce Type: new Abstract: Autoregressive rigging models such as UniRig and SkinTokens perform well on articulated characters, but their ability to generalize to plant structures

Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging

arXiv:2608.00586v1 Announce Type: new Abstract: Despite the widespread adoption of foundation models as feature extractors for medical imaging, relatively little is understood about how different pret

Retrieval-Augmented Interpretable Learning: Towards Task-Specific Zero-Shot Models in Healthcare

arXiv:2607.17508v2 Announce Type: replace Abstract: We introduce Retrieval-Augmented Interpretable Learning (RAIL), a probabilistic meta-learning framework for zero-shot generation of task-specific in

applicationsarxiv-cs-lg

Unleashing the Potential of Large Language Models: A Blueprint for Real-Time, Enterprise-Ready Deployments

arXiv:2608.00419v1 Announce Type: cross Abstract: Large language models deployed in real-time, regulated settings face knowledge staleness, catastrophic forgetting, hallucination, and weak feedback lo

safetyarxiv-cs-cl

VARPose: Flexible 2D Pose Densification via Visual Autoregressive Modeling for Enhanced 3D Lifting

arXiv:2608.02214v1 Announce Type: new Abstract: Visual AutoRegressive Modeling (VAR) has excelled in natural image generation via next-scale prediction, but its use on topology-structured data like hu

ActionParty: Multi-Subject Action Binding in Generative Video Games

model-releasesarxiv-cs-ai

arXiv:2604.02330v2 Announce Type: replace-cross Abstract: Recent advances in video diffusion have enabled the development of 'world models' capable of simulating interactive environments. However, the

An analysis of machine learning approaches for enhancing decision-making in complex discrete choice tasks

arXiv:2607.28854v1 Announce Type: new Abstract: Discrete choice modeling is a common tool used for preference elicitation during policy-making, but this is typically done through parametric models. Ma

safetyarxiv-cs-lg

AniCrafter: Customizing Realistic Human-Centric Animation via Avatar-Background Conditioning in Video Diffusion Models

arXiv:2505.20255v3 Announce Type: replace Abstract: Recent advances in video diffusion models have substantially enhanced character animation techniques. However, existing methods primarily depend on

Beyond Feature and Structure Alignment: Learning Transferable Propagation Knowledge for Graph Foundation Models

arXiv:2607.28980v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) have recently emerged as a promising paradigm for enabling knowledge transfer across diverse domains. Unlike traditional

safetyarxiv-cs-lg

Can AI Evaluate AI Scientists? A Benchmarking Study of Autonomous Research Generation Systems Using Automated Multi-Model Review

model-releasesarxiv-cs-ai

arXiv:2607.28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery. However, evaluating and compari

On the Efficacy of Self-Supervised Point Cloud Encoders for Efficient 3D Large Language Models

arXiv:2607.29136v1 Announce Type: new Abstract: 3D point cloud-language models (3D-LLMs) enable 3D understanding by pairing point cloud encoders with large language models, but existing methods rely o

QR-Structured Thermal Triggers for Targeted Semantic Attacks on Infrared Vision-Language Models

arXiv:2607.29445v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) extend thermal perception to open-vocabulary classification, image captioning, and visual question answering

safetyarxiv-cs-ai

The Morphological Core of Dungan: A Two-Dialect Finite-State Model and a Multi-Genre Evaluation

model-releasesarxiv-cs-cl

arXiv:2607.28766v1 Announce Type: new Abstract: Dungan, a Sinitic language of Central Asia written in a Cyrillic-based script, is described in detail in the grammatical literature, yet the quantitativ

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

arXiv:2607.28617v1 Announce Type: cross Abstract: System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout com

AuricularWorld: Hierarchical Action-Guided World Modeling for Fine-Grained Auricular Structure Segmentation from CT Scans

arXiv:2607.28487v1 Announce Type: new Abstract: Fine-grained segmentation of auricular structures in CT is challenging because the ear occupies a small image region, cartilage boundaries are highly ir

tutorialsarxiv-cs-cv

Beyond KV Reconstruction: Functional Reconstruction for MLA Draft Models in Speculative Decoding

arXiv:2607.27269v1 Announce Type: new Abstract: Multi-head latent attention (MLA) is increasingly important for long-context LLM inference because compact latent states replace the growing key-value (

BioPro: Towards Difference-Aware Gender Fairness for Vision-Language Models

arXiv:2512.00807v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) inherit significant social biases from their training data, notably in gender representation. Current fairness interve

safetyarxiv-cs-ai

Capturing Token Tendencies for Training-Free Token Pruning in Multimodal Large Language Models

arXiv:2607.28341v1 Announce Type: new Abstract: While visual token pruning is essential for efficient Multimodal Large Language Models (MLLMs), existing training-free methods suffer from a critical li

local-aiarxiv-cs-cv

CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations

arXiv:2505.04999v2 Announce Type: replace-cross Abstract: Learning robot control policies from demonstrations typically requires action-labeled expert data, which is expensive to collect through teleo

applicationsarxiv-cs-lg

Divergence Decoding: Training-Free Capability Fusion

arXiv:2607.27248v1 Announce Type: cross Abstract: While large language models excel in reasoning, these generalists often lack knowledge for specialized scientific domains. Conversely, domain models~(

EgoGenesis: Egocentric World-Action Modeling with Online Anchored Projective Memory and Action-3D RoPE

arXiv:2607.28243v1 Announce Type: new Abstract: Egocentric video offers rich manipulation experience for embodied AI, yet collecting diverse egocentric data across scenes, objects, motions, and embodi

Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model

arXiv:2607.10285v2 Announce Type: replace Abstract: We study how unsupervised autoencoders trained on microscopic spin configurations from the Ising model learn macroscopic, theory-relevant variables

tutorialsarxiv-cs-lg

Lightning OPD 2.0: Mitigating Style Bias in Cross-Teacher On-Policy Distillation for Large Reasoning Models

model-releasesarxiv-cs-cl

arXiv:2607.28449v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense token-level supervision from a teacher, but its effectiveness can depend on teacher consistency, meaning tha

LightRot: A Light-Weighted Rotation Scheme and Architecture for Accurate Low-Bit Large Language Model Inference

arXiv:2607.27704v1 Announce Type: cross Abstract: As large language models (LLMs) continue to demonstrate exceptional capabilities across various domains, the challenge of achieving energy-efficient a

local-aiarxiv-cs-lg

LM-GRASP: Instance-Specific Language Models for Combinatorial Construction via Online Imitation Learning

arXiv:2607.28135v1 Announce Type: new Abstract: Machine learning for combinatorial optimization typically relies on neural constructors trained via reinforcement learning on large offline datasets for

Rethinking LLM-Judged Helpfulness as a Pedagogy Signal: A Pre-Registered Audit Across Tutor Models

model-releasesarxiv-cs-cl

arXiv:2607.28128v1 Announce Type: new Abstract: LLM tutoring poses a measurement problem: can a general-purpose helpfulness rubric distinguish direct answer-giving from pedagogical guidance? We audit

Challenges and proposed solutions in modeling multimodal medical data: A systematic review

arXiv:2505.06945v5 Announce Type: replace Abstract: Multimodal data modeling has emerged as a powerful approach in clinical research, enabling the integration of diverse data types such as imaging, ge

tutorialsarxiv-cs-lg

DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models

arXiv:2607.26891v1 Announce Type: new Abstract: Sequence labeling is a fine-grained information extraction task, yet existing large language model-based approaches suffer from insufficient domain alig

safetyarxiv-cs-cl

Explicit Kinematic Guidance from Analytic Concepts for Vision-Language-Action Models

arXiv:2607.26513v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models rely mainly on 2D inputs, neglecting the rich object structural information and commonsense knowledge inhere

tutorialsarxiv-cs-ro

LumaGuide: Distribution Shaping for Training-Free HDR Generation in Diffusion Models

arXiv:2607.26237v1 Announce Type: new Abstract: Pretrained diffusion models generate realistic images but are constrained by the statistical biases of their training data, limiting their ability to pr

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation

arXiv:2607.27058v1 Announce Type: new Abstract: Currently, autonomous driving object detection models face significant data scarcity and generalization challenges when navigating complex Chinese rural

local-aiarxiv-cs-cv

Structurally Separated Uncertainty in Supervised Latent Variable Models

arXiv:2602.11219v2 Announce Type: replace Abstract: Predictive uncertainty is commonly decomposed into epistemic and aleatoric components, but standard decompositions often produce strongly correlated

TPD: Temporal Prior Decoupling for Text-to-Video Diffusion Models

arXiv:2607.26706v1 Announce Type: new Abstract: Text-to-video diffusion models generate temporally coherent content from natural language, yet when a prompt describes an early scene that persists whil

Balanced Soft mixture-of-expert model for Glaucoma Detection

arXiv:2607.25324v1 Announce Type: cross Abstract: Glaucoma is a group of eye diseases that damage the optic nerve, often caused by elevated intraocular pressure. It is a leading cause of irreversible

tutorialsarxiv-cs-ai

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Beyond Epistemia: Epistemic Schizologia and Large Language Models as Techno-Semiotic Machines

arXiv:2607.25620v1 Announce Type: new Abstract: Quattrociocchi and colleagues warn that the fluent outputs of large language models may allow linguistic plausibility to substitute for epistemic evalua

agentsarxiv-cs-ai

Desktop-Delta Bench: Do Computer-Use Models Understand Desktop GUI Transitions?

model-releasesarxiv-cs-ai

arXiv:2607.26041v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly act through desktop GUIs to complete long-horizon tasks. Current benchmarks primarily measure end-task success o

Multi-Fidelity Learning with Shallow Recurrent Decoders for Multi-Physics Applications

arXiv:2606.05202v2 Announce Type: replace-cross Abstract: In reactor physics, neutronics and multi-physics phenomena can be modelled at different fidelity levels. High-fidelity models based on the Bol