Search: “models”

Language Model Networks: Supervision-Efficient Learning through Dense Communication

arXiv:2505.12741v2 Announce Type: replace Abstract: Language models are increasingly used not only as standalone predictors but also as components in larger inference systems, from test-time reasoning

applicationsarxiv-cs-ai

Research

Mind the Gap: How Elicitation Protocols Shape the Stated-Revealed Preference Gap in Language Models

DGX agent

arXiv:2601.21975v2 Announce Type: replace Abstract: Recent work identifies a stated-revealed (SvR) preference gap in language models (LMs): a mismatch between the values models endorse and the choices

researcharxiv-cs-ai

14 May 2026

Neural Surrogate Forward Modelling For Electrocardiology Without Explicit Intracellular Conductivity Tensor

arXiv:2605.13366v1 Announce Type: new Abstract: Accurate forward modelling is essential for non-invasive cardiac electrophysiology, particularly in atrial fibrillation, where electrical activation is

PaMM: Periodic Motif Memory for Atomistic Models with an Explicit Local-Structure Interface

arXiv:2605.13297v1 Announce Type: new Abstract: Periodic crystals repeatedly instantiate similar local coordination motifs across translated cells and chemically related structures, but current equiva

Radial Compensation: Fixing Radius Distortion in Chart-Based Generative Models on Riemannian Manifolds

arXiv:2511.14056v2 Announce Type: replace-cross Abstract: We study the base distribution in chart-based generative models on Riemannian manifolds. Standard methods sample in Euclidean tangent space an

researcharxiv-cs-ai

A Causal Language Modeling Detour Improves Encoder Continued Pretraining

arXiv:2605.12438v1 Announce Type: new Abstract: When adapting an encoder to a new domain, the standard approach is to continue training with Masked Language Modeling (MLM). We show that temporarily sw

A nonlinear extension of parametric model embedding for dimensionality reduction in parametric shape design

arXiv:2605.11759v1 Announce Type: cross Abstract: Dimensionality reduction is essential in simulation-based shape design, where high-dimensional parameterizations hinder optimization, surrogate modeli

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning

arXiv:2605.12197v1 Announce Type: new Abstract: Leveraging Graph Neural Networks (GNNs) as graph encoders and aligning the resulting representations with Large Language Models (LLMs) through alignment

Control of Fully Actuated Aerial Vehicles: A Comparison of Model-based and Sensor-based Dynamic Inversion

model-releasesarxiv-cs-ro

arXiv:2605.12071v1 Announce Type: new Abstract: Fully actuated multirotor platforms decouple translational force generation from vehicle attitude, enabling independent control of position and orientat

Tutorials

Do AI models really learn physics, or just learn what physics looks like? Flatiron's @_helenqu, with @PolymathicAI & CDS researchers includi…

Do AI models really learn physics, or just learn what physics looks like? Flatiron's @_helenqu, with @PolymathicAI & CDS researchers including @ylecun, finds that models predicting in latent space rec

tutorialsyann-lecun--x

Enabling Performant and Flexible Model-Internal Observability for LLM Inference

arXiv:2605.11093v1 Announce Type: new Abstract: Today's inference-time workloads increasingly depend on timely access to a model's internal states. We present DMI-Lib, a high-speed deep model inspecto

From Message-Passing to Linearized Graph Sequence Models

arXiv:2605.12358v1 Announce Type: new Abstract: Message-passing based approaches form the default backbone of most learning architectures on graph-structured data. However, the rapid progress of moder

Gradient-Boosted Decision Tree for Listwise Context Model in Multimodal Review Helpfulness Prediction

model-releasesarxiv-cs-cl

arXiv:2305.12678v3 Announce Type: replace Abstract: Multimodal Review Helpfulness Prediction (MRHP) aims to rank product reviews based on predicted helpfulness scores and has been widely applied in e-

Grid Games: The Power of Multiple Grids for Quantizing Large Language Models

arXiv:2605.12327v1 Announce Type: new Abstract: A major recent advance in quantization is given by microscaled 4-bit formats such as NVFP4 and MXFP4, quantizing values into small groups sharing a scal

Hyperbolic Concept Bottleneck Models

arXiv:2605.06440v2 Announce Type: replace-cross Abstract: Concept Bottleneck Models (CBMs) have become a popular approach to enable interpretability in neural networks by constraining classifier input

Interactive State Space Model with Cross-Modal Local Scanning for Depth Super-Resolution

arXiv:2605.11934v1 Announce Type: new Abstract: Guided depth super-resolution (GDSR) reconstructs HR depth maps from LR inputs with HR RGB guidance. Existing methods either model each modality indepen

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation

arXiv:2510.17062v2 Announce Type: replace Abstract: While reasoning-based large language models excel at complex tasks through an internal, structured thinking process, a concerning phenomenon has eme

safetyarxiv-cs-cl

Lite3R: A Model-Agnostic Framework for Efficient Feed-Forward 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.11354v1 Announce Type: new Abstract: Transformer-based 3D reconstruction has emerged as a powerful paradigm for recovering geometry and appearance from multi-view observations, offering str

Agents

MAC: Masked Agent Collaboration Boosts Large Language Model Medical Decision-Making

arXiv:2507.21159v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have proven effective in artificial intelligence, where the multi-agent system (MAS) holds considerable promise f

agentsarxiv-cs-lg

Modality-Inconsistent Continual Learning of Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2412.13050v2 Announce Type: replace-cross Abstract: In this paper, we introduce Modality-Inconsistent Continual Learning (MICL), a new continual learning scenario for Multimodal Large Language M

more demos on Interaction Models collaboratively doing system design, reading papers, fact-checking with live generative UI

researchsoumith-chintala--x

more demos on Interaction Models collaboratively doing system design, reading papers, fact-checking with live generative UI 1. (System design) - The Interaction Models see your screen and collaborates

Neural ARFIMA model for forecasting BRIC exchange rates with long memory

arXiv:2509.06697v2 Announce Type: replace-cross Abstract: Accurate forecasting of exchange rates remains a persistent challenge, particularly for emerging economies such as Brazil, Russia, India, and

Oscillators Are All You Need: Irregular Time Series Modelling via Damped Harmonic Oscillators with Closed-Form Solutions

arXiv:2602.12139v2 Announce Type: replace Abstract: Transformers excel at time series modelling through attention mechanisms that capture long-term temporal patterns. However, they assume uniform time

Partial Model Sharing Improves Byzantine Resilience in Federated Conformal Prediction

arXiv:2605.11684v1 Announce Type: new Abstract: We propose a Byzantine-resilient federated conformal prediction (FCP) method that leverages partial model sharing, where only a subset of model paramete

Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks

arXiv:2509.06701v2 Announce Type: replace Abstract: We develop a theory of intelligent agency grounded in probabilistic modeling for neural models. Agents are represented as outcome distributions with

ReAD: Reinforcement-Guided Capability Distillation for Large Language Models

arXiv:2605.11290v1 Announce Type: new Abstract: Capability distillation applies knowledge distillation to selected model capabilities, aiming to compress a large language model (LLM) into a smaller on

Scalable Token-Level Hallucination Detection in Large Language Models

arXiv:2605.12384v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities, but they still frequently produce hallucinations. These hallucinations are diffi

SoK: Unlearnability and Unlearning for Model Dememorization

arXiv:2605.11592v1 Announce Type: new Abstract: Advanced model dememorization methods, including availability poisoning (unlearnability) and machine unlearning, are emerging as key safeguards against

Local Ai

SOMA: Efficient Multi-turn LLM Serving via Small Language Model

arXiv:2605.11317v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in multi-turn dialogue settings where preserving conversational context across turns is essential

local-aiarxiv-cs-cl

Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey

arXiv:2304.10891v2 Announce Type: replace-cross Abstract: Transformer-based models are becoming a central paradigm in autonomous driving because they can capture long-range spatial dependencies, multi

safetyarxiv-cs-cv

Variance-aware Reward Modeling with Anchor Guidance

arXiv:2605.11865v1 Announce Type: cross Abstract: Standard Bradley--Terry (BT) reward models are limited when human preferences are pluralistic. Although soft preference labels preserve disagreement i

applicationsarxiv-cs-lg

Agents

We’re training models wrong and it’s due to chatGPT. Even the modern coding agents used daily still use message-based exchanges: They send m…

We’re training models wrong and it’s due to chatGPT. Even the modern coding agents used daily still use message-based exchanges: They send messages to users, to themselves (CoT) and to tools, and rece

agentsjeremy-howard--x

Active Testing of Large Language Models via Approximate Neyman Allocation

arXiv:2605.10075v1 Announce Type: new Abstract: Large language models (LLMs) require reliable evaluation from pre-training to test-time scaling, making evaluation a recurring rather than one-off cost.

researcharxiv-cs-ai

ALAM: Algebraically Consistent Latent Transitions for Vision-Language-Action Models

arXiv:2605.10819v1 Announce Type: cross Abstract: Vision-language-action (VLA) models remain constrained by the scarcity of action-labeled robot data, whereas action-free videos provide abundant evide

safetyarxiv-cs-ai

Beyond Majority Voting: Agreement-Based Clustering to Model Annotator Perspectives in Subjective NLP Tasks

arXiv:2605.09955v1 Announce Type: new Abstract: Disagreement in annotation is a common phenomenon in the development of NLP datasets and serves as a valuable source of insight. While majority voting r

Complete Evidence Extraction with Model Ensembles: A Case Study on Medical Coding

arXiv:2511.07055v3 Announce Type: replace Abstract: High-stakes decisions informed by decision support systems require explicit evidence. While prior work focuses on short sufficient evidence, regulat

applicationsarxiv-cs-cl

Consistent Projection of Langevin Dynamics: Preserving Thermodynamics and Kinetics in Coarse-Grained Models

arXiv:2512.03706v2 Announce Type: replace-cross Abstract: Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dyn

Dimensional Coactivation for Representational Consistency in Frozen Vision Foundation Models

arXiv:2605.08249v1 Announce Type: new Abstract: Frozen vision foundation models do not merely extract features; they organize images through a learned coordinate system. We ask whether that coordinate

Distilling 3D Spatial Reasoning into a Lightweight Vision-Language Model with CoT

arXiv:2605.09719v1 Announce Type: cross Abstract: Large-scale 3D vision-language models (VLMs) like LLaVA-3D offer strong spatial reasoning but are difficult to deploy due to high computational costs.

applicationsarxiv-cs-ai

Empty SPACE: Cross-Attention Sparsity for Concept Erasure in Diffusion Models

arXiv:2605.10198v1 Announce Type: cross Abstract: Erasing specific concepts from text-to-image diffusion models is essential for avoiding the generation of copyrighted and explicit content. Closed-for

researcharxiv-cs-ai

Local Ai

ExecuTorch -- A Unified PyTorch Solution to Run AI Models On-Device

arXiv:2605.08195v1 Announce Type: new Abstract: Local execution of AI on edge devices is important for low latency and offline operation. However, deploying models on diverse hardware remains fragment

local-aiarxiv-cs-lg

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models

model-releasesarxiv-cs-ai

arXiv:2605.09081v1 Announce Type: cross Abstract: We introduce the first universal pretraining corpus for industrial time-series data: FactoryNet. 51M datapoints across 23k end-to-end task executions

Tutorials

From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models

arXiv:2605.09949v1 Announce Type: new Abstract: Understanding how chemical language models (CLMs) learn chemical meaning from molecular string representations, rather than only surface-level string pa

tutorialsarxiv-cs-lg

GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction

model-releasesarxiv-cs-ai

arXiv:2605.09973v1 Announce Type: cross Abstract: Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains

How open model ecosystems compound

This article examines how open-source AI model ecosystems create compounding effects through community contributions, fine-tuning, and iterative improvements that accelerate innovation and accessibili

researchinterconnects

Learning stochastic multiscale models through normalizing flows

arXiv:2605.09718v1 Announce Type: cross Abstract: Many systems in physics, engineering, and biology exhibit multiscale stochastic dynamics, where low-dimensional slow variables evolve under the influe

Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistants

arXiv:2508.16070v3 Announce Type: replace Abstract: Approximately 283 million people worldwide live with visual impairments, motivating increasing research into leveraging Visual Language Models (VLMs

LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programs

model-releasesarxiv-cs-ai

arXiv:2605.10401v1 Announce Type: new Abstract: Efficient branching policies are essential for accelerating Mixed Integer Linear Programming (MILP) solvers. Their design has long relied on hand-crafte