Search: “models”

arXiv:2603.14392v2 Announce Type: replace Abstract: Trajectory world models play a crucial role in robotic dynamics learning, planning, and control. While recent works have explored trajectory world m

applicationsarxiv-cs-lg

21 May 2026

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Research

Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction

DGX agent

arXiv:2506.17036v2 Announce Type: replace-cross Abstract: Modern industrial systems are often subject to multiple failure modes, and their conditions are monitored by multiple sensors, generating mult

researcharxiv-cs-lg

20 May 2026

Chessformer: A Unified Architecture for Chess Modeling

arXiv:2605.19091v1 Announce Type: new Abstract: Chess has long served as a canonical testbed for artificial intelligence, but modeling approaches for its central tasks have diverged. Maximizing playin

Neural Operators for Design-Space Surrogate Modeling of Tendon-Actuated Continuum Robots

arXiv:2605.19104v1 Announce Type: cross Abstract: Continuum robots enable dexterous manipulation in constrained environments, but require accurate and efficient models for real-time manipulation and c

Probabilistic Tiny Recursive Model

arXiv:2605.19943v1 Announce Type: new Abstract: Tiny Recursive Models (TRM) solve complex reasoning tasks with a fraction of the parameters of modern large language models (LLMs) by iteratively refini

Recursive Entropic Risk Optimization in Discounted MDPs: Sample Complexity Bounds with a Generative Model

arXiv:2506.00286v3 Announce Type: replace-cross Abstract: We study risk-sensitive reinforcement learning in finite discounted MDPs with recursive entropic risk measures (ERM), where the risk parameter

Shaping the Prior: How Synthetic Task Distributions Determine Tabular Foundation Model Quality

arXiv:2605.18971v1 Announce Type: cross Abstract: What determines the quality of a tabular foundation model? Unlike language or vision, tabular foundation models acquire their inductive biases almost

CrossView Suite: Harnessing Cross-view Spatial Intelligence of MLLMs with Dataset, Model and Benchmark

arXiv:2605.18621v1 Announce Type: cross Abstract: Spatial intelligence requires multimodal large language models (MLLMs) to move beyond single-view perception and reason consistently about objects, vi

Data-Driven Dynamic Modeling of a Tendon-Actuated Continuum Robot

arXiv:2605.18720v1 Announce Type: new Abstract: Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. T

researcharxiv-cs-ro

Applications

DiffWind: Physics-Informed Differentiable Modeling of Wind-Driven Object Dynamics

arXiv:2603.09668v2 Announce Type: replace Abstract: Modeling wind-driven object dynamics from video observations is highly challenging due to the invisibility and spatio-temporal variability of wind,

applicationsarxiv-cs-cv

ECG-WM: A Physiology-Informed ECG World Model for Clinical Intervention Simulation

arXiv:2605.17580v1 Announce Type: new Abstract: Electrocardiogram (ECG)-based models have achieved strong performance in diagnostic tasks, yet they remain limited in modeling how cardiac dynamics evol

FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction

arXiv:2605.18055v1 Announce Type: cross Abstract: Predicting spatial gene expression from routine H&E enables large-scale molecular profiling, yet current models treat this as isolated pointwise tasks

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion

arXiv:2605.17759v1 Announce Type: new Abstract: To circumvent the inherent fidelity bottlenecks and optimization misalignment of VAE-based latent diffusion, pixel-space diffusion models have emerged a

local-aiarxiv-cs-cv

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction

arXiv:2605.16927v1 Announce Type: new Abstract: Clinical decision-making is a feedback system where risk estimates influence treatment, which in turn changes disease trajectories, and both shape clini

Lance: Unified Multimodal Modeling by Multi-Task Synergy

arXiv:2605.18678v1 Announce Type: cross Abstract: We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather t

One Model, Two Roles: Emergent Specialization in a Shared Recurrent Transformer

arXiv:2605.17811v1 Announce Type: cross Abstract: Can a shared-weight recurrent Transformer develop distinct internal roles without being partitioned into separate modules? We study this in Asymmetric

Retrieval and competition: how a protein foundation model starts a protein

arXiv:2605.16331v1 Announce Type: cross Abstract: Protein language models are increasingly used to guide experimental and clinical decisions, yet it is often unclear whether a confident prediction ref

Structured Neural Marked Point Processes for Interpretable Event Interaction Modeling

model-releasesarxiv-cs-lg

arXiv:2605.17568v1 Announce Type: new Abstract: Multi-class event streams arise in numerous real-world applications, where uncovering structured, interpretable inter-event relationships, together with

Hardware

Systematic Optimization of Real-Time Diffusion Model Inference on Apple M3 Ultra

arXiv:2605.16259v1 Announce Type: cross Abstract: While real-time image generation using diffusion models has advanced rapidly on NVIDIA GPUs, systematic optimization research on non-CUDA platforms su

hardwarearxiv-cs-ai

WOW-Seg: A Word-free Open World Segmentation Model

model-releasesarxiv-cs-cv

arXiv:2605.16903v1 Announce Type: new Abstract: Open world image segmentation aims to achieve precise segmentation and semantic understanding of targets within images by addressing the infinitely open

MIND: Decoupling Model-Induced Label Noise via Latent Manifold Disentanglement

arXiv:2605.16081v1 Announce Type: cross Abstract: The paradigm of learning from automatic annotations driven by pre-trained experts and Foundation Models dominates data-hungry applications. However, i

local-aiarxiv-cs-cv

Overfitting has a limitation: a model-independent generalization gap bound based on Renyi entropy

arXiv:2506.00182v3 Announce Type: replace-cross Abstract: Will further scaling up of machine learning models continue to bring success? A significant challenge in answering this question lies in under

researcharxiv-cs-lg

RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning

model-releasesarxiv-cs-cl

arXiv:2512.04457v2 Announce Type: replace Abstract: Removing specific data influence from large language models (LLMs) remains challenging, as retraining is costly and existing approximate unlearning

Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers

arXiv:2505.12601v2 Announce Type: replace Abstract: As large language models (LLMs) grow in scale and specialization, routing--selecting the best model for a given input--has become essential for effi

local-aiarxiv-cs-lg

EponaV2: Driving World Model with Comprehensive Future Reasoning

arXiv:2605.14696v1 Announce Type: new Abstract: Data scaling plays a pivotal role in the pursuit of general intelligence. However, the prevailing perception-planning paradigm in autonomous driving rel

safetyarxiv-cs-cv

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

arXiv:2605.14950v1 Announce Type: new Abstract: Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action gener

safetyarxiv-cs-cv

FedStain: Modeling Higher-Order Stain Statistics for Federated Domain Generalization in Computational Pathology

model-releasesarxiv-cs-cv

arXiv:2605.14590v1 Announce Type: new Abstract: Robust whole-slide image (WSI) analysis under strict data-governance remains challenging due to substantial cross-institutional stain heterogeneity. Dom

Quantitative Video World Model Evaluation for Geometric-Consistency

arXiv:2605.15185v1 Announce Type: cross Abstract: Generative video models are increasingly studied as implicit world models, yet evaluating whether they produce physically plausible 3D structure and m

RePack then Refine: Efficient Diffusion Transformer with Vision Foundation Model

arXiv:2512.12083v3 Announce Type: replace Abstract: Semantic-rich features from Vision Foundation Models (VFMs) have been leveraged to enhance Latent Diffusion Models (LDMs). However, raw VFM features

researcharxiv-cs-cv

A Markov Categorical Framework for Language Modeling

arXiv:2507.19247v5 Announce Type: replace-cross Abstract: Autoregressive language models achieve remarkable performance, yet a unified theory explaining their internal mechanisms, how training shapes

Agents

CADDesigner: Conceptual CAD Model Generation with a General-Purpose Agent

arXiv:2508.01031v5 Announce Type: replace Abstract: Computer-Aided Design (CAD) is widely used for conceptual design and parametric 3D modeling, but typically requires a high level of expertise from d

agentsarxiv-cs-ai

Compact Latent Manifold Translation: A Parameter-Efficient Foundation Model for Cross-Modal and Cross-Frequency Physiological Signal Synthesis

arXiv:2605.13248v1 Announce Type: cross Abstract: The analysis of physiological time series, such as electrocardiograms (ECG) and photoplethysmograms (PPG), is persistently hindered by modality and fr

Continual Learning with Multilingual Foundation Model

arXiv:2605.13415v1 Announce Type: cross Abstract: This paper presents a multi-stage framework for detecting reclaimed slurs in multilingual social media discourse. It addresses the challenge of identi

Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold

arXiv:2602.06021v2 Announce Type: replace-cross Abstract: We study a data-dependent notion of diffusion-model generalization: when a model does not memorize the training set, where do its generated sa

Applications

It's not the Language Model, it's the Tool: Deterministic Mediation for Scientific Workflows

arXiv:2605.13245v1 Announce Type: new Abstract: Language models can produce convincing scientific analyses, but repeated generations on the same data do not guarantee the same result. A researcher may

applicationsarxiv-cs-ai

KAST-BAR: Knowledge-Anchored Semantically-Dynamic Topology Brain Autoregressive Modeling for Universal Neural Interpretation

arXiv:2605.13133v1 Announce Type: new Abstract: While EEG foundation models have shown significant potential in universal neural decoding across tasks, their advancement remains constrained by the ina

local-aiarxiv-cs-lg

Agents

Mechanism Plausibility in Generative Agent-Based Modeling

arXiv:2605.12824v1 Announce Type: cross Abstract: Large language models (LLMs) can generate high-level diverse phenomena without explicitly programmed rules. This capability has led to their adoption

agentsarxiv-cs-ai

QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modeling

arXiv:2605.13833v1 Announce Type: cross Abstract: Modeling long-range dependencies in sequential data remains a central challenge in machine learning. Transformers address this challenge through atten

researcharxiv-cs-cv

The Score-Difference Flow for Implicit Generative Modeling

arXiv:2304.12906v4 Announce Type: replace Abstract: Implicit generative modeling (IGM) aims to produce samples of synthetic data matching the characteristics of a target data distribution. Recent work

researcharxiv-cs-lg

What properties of reasoning supervision are associated with improved downstream model quality?

arXiv:2605.13290v1 Announce Type: new Abstract: Validating training data for reasoning models typically requires expensive trial-and-error fine-tuning cycles. In this work, we investigate whether the

A Study on Hidden Layer Distillation for Large Language Model Pre-Training

model-releasesarxiv-cs-cl

arXiv:2605.11513v1 Announce Type: new Abstract: Knowledge Distillation (KD) is a critical tool for training Large Language Models (LLMs), yet the majority of research focuses on approaches that rely s

Active inference as a unified model of collision avoidance behavior in human drivers

arXiv:2506.02215v5 Announce Type: replace Abstract: Collision avoidance -- involving a rapid threat detection and quick execution of the appropriate evasive maneuver -- is a critical aspect of driving

researcharxiv-cs-ro

DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion

arXiv:2505.18780v3 Announce Type: replace-cross Abstract: Achieving versatile humanoid locomotion with a single policy presents a critical scalability challenge. Prevailing methods often rely on disti

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records

arXiv:2605.12335v1 Announce Type: cross Abstract: Electronic Health Records (EHR) contain rich longitudinal patient information and are widely used in predictive modeling applications. However, effect

Express Your Doubts -- Probabilistic World Modeling Should not be Based on Token logprobs

arXiv:2505.02072v2 Announce Type: replace Abstract: Language modeling has shifted in recent years from a distribution over strings to prediction models with textual inputs and outputs for general-purp

researcharxiv-cs-cl

See What Matters: Differentiable Grid Sample Pruning for Generalizable Vision-Language-Action Model

model-releasesarxiv-cs-cv

arXiv:2605.11817v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown remarkable promise in robotics manipulation, yet their high computational cost hinders real-time deploy

Structural Interpretations of Protein Language Model Representations via Differentiable Graph Partitioning

arXiv:2605.10985v1 Announce Type: new Abstract: Protein language models such as ESM-2 learn rich residue representations that achieve strong performance on protein function prediction, but their featu

local-aiarxiv-cs-lg

Vision-aligned Latent Reasoning for Multi-modal Large Language Model

arXiv:2602.04476v2 Announce Type: replace Abstract: Despite recent advancements in Multi-modal Large Language Models (MLLMs) on diverse understanding tasks, these models struggle to solve problems whi

researcharxiv-cs-cv