Search: “models”

Truthful AI Advisors: A Pre-Specified Benchmark for Large Language Model Honesty Under Preference Misalignment

arXiv:2606.01456v1 Announce Type: cross Abstract: Large language models are increasingly deployed as advisors whose objective is not aligned with the user's: recommenders optimize for engagement, sale

2 Jun 2026

Model Releases

CodeGolf Bench: A Multi-Language Benchmark for Evaluating Concise Code Generation Capabilities of Large Language Models

DGX agent

arXiv:2605.30394v1 Announce Type: cross Abstract: This paper introduces Code Bench, a benchmark capable of evaluating Large Language Models (LLMs) concise code generation abilities in 60 programming l

model-releasesarxiv-cs-ai

1 Jun 2026

DriveMA: Driving Vision-Language-Action Models with verifiable Meta-Actions

arXiv:2605.31271v1 Announce Type: new Abstract: Driving Vision-Language-Action Models (Driving VLAs) aim to use language to improve end-to-end planning, but the language-action gap limits this promise

Float8@2bits: Entropy Coding Enables Data-Free Model Compression

arXiv:2601.22787v2 Announce Type: replace Abstract: Post-training compression is currently divided into two contrasting regimes. On the one hand, fast, data-free, and model-agnostic methods (e.g., NF4

ImmigrationQA: A Source-Grounded Dataset and Small-Model Adaptation for U.S. Immigration Law

arXiv:2605.30589v1 Announce Type: cross Abstract: U.S. immigration law spans thousands of pages of official policy, federal regulations, and procedural guidance that change frequently and carry high s

Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions

arXiv:2605.31586v1 Announce Type: cross Abstract: Grasping the semantics of rare constructions (form-meaning pairings) has been shown to be a challenging problem that has currently only been solved by

LiMuon: Light and Fast Muon Optimizer for Large Models

arXiv:2509.14562v3 Announce Type: replace Abstract: Large models recently are widely applied in machine learning, so efficient training of large models has received widespread attention. More recently

Tutorials

Representation Forcing for Bottleneck-Free Unified Multimodal Models

arXiv:2605.31604v1 Announce Type: new Abstract: Unified multimodal models (UMMs) aim to handle perception and generation in a single model. Yet existing UMMs still rely on a frozen, separately pretrai

tutorialsarxiv-cs-cv

SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling

arXiv:2510.05115v3 Announce Type: replace Abstract: Large language models (LLMs) have opened new paradigms in optimization modeling by enabling the generation of executable solver code from natural la

Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation

arXiv:2605.29992v1 Announce Type: new Abstract: Sentence embeddings are a foundational component for semantic search, clustering, classification, and retrieval-augmented generation. This paper present

Aggregate Models, Not Explanations: Improving Feature Importance Estimation

arXiv:2602.11760v2 Announce Type: replace-cross Abstract: Feature-importance methods show promise in transforming machine learning models from predictive engines into tools for scientific discovery. H

Contrastive Representation Regularization for Vision-Language-Action Models

arXiv:2510.01711v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in robot manipulation by leveraging rich representations from pre-trained V

Improving Full Waveform Inversion in Large Model Era

arXiv:2603.00377v2 Announce Type: replace Abstract: Full Waveform Inversion (FWI) is a highly nonlinear and ill-posed problem that aims to recover subsurface velocity maps from surface-recorded seismi

Safety

In-Context Reward Adaptation for Robust Preference Modeling

arXiv:2605.30323v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) typically relies on static reward models to align Large Language Models with human preferences. Howe

safetyarxiv-cs-ai

libhmm: A Modern C++20 Library for Hidden Markov Models with Correct MLE Emission M-Steps

arXiv:2605.29208v1 Announce Type: cross Abstract: We describe libhmm, a C++20 library for Hidden Markov Model parameter estimation, sequence decoding, and model selection. libhmm addresses two gaps in

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation

arXiv:2605.29280v1 Announce Type: cross Abstract: Knowledge distillation (KD) transfers a single scalar prediction from a large foundation model (FM) to compact vertical models (VMs), suffering from d

MechELK: A Mechanistic Interpretability Framework for Eliciting Latent Knowledge in Large Language Models

arXiv:2605.28825v1 Announce Type: new Abstract: Large language models (LLMs) frequently encode factual and reasoning knowledge in their internal representations that is not faithfully reflected in the

Mitigating Hallucination in Vision-Language Models through Barrier-Regulated Adaptive Closed-form Steering

arXiv:2605.29881v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate objects that are not present in the input image, largely because visual grounding weakens as de

Model Merging by Output-Space Projection

arXiv:2605.29101v1 Announce Type: new Abstract: Model merging combines fine-tuned checkpoints into a single multi-task model without retraining. Existing methods - such as task arithmetic, model soups

Agents

open models are having a moment!

open models are having a moment! The latest finding in the LangSmith Signal: Open Models are having a moment. 1 in 3 AI teams ran an open-weights model in April 2026, up from 1 in 5 nine months ago. T

agentsharrison-chase--x

Agents

open models will become a huge force for coding.

open models will become a huge force for coding. The latest finding in the LangSmith Signal: Open Models are having a moment. 1 in 3 AI teams ran an open-weights model in April 2026, up from 1 in 5 ni

agentsharrison-chase--x

Procedural Pretraining: Warming Up Language Models with Abstract Data

arXiv:2601.21725v2 Announce Type: replace Abstract: Pretraining language models directly on web-scale corpora is the de facto paradigm. We study an alternative where the model is initially exposed to

researcharxiv-cs-cl

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

arXiv:2605.30280v1 Announce Type: cross Abstract: Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented cap

ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving

arXiv:2605.29114v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models with integrated reasoning have been proposed for end-to-end autonomous driving, assuming a tight coupling between

When Models Disagree: Rethinking LLM Evaluation for Public Comment Analysis

arXiv:2605.29025v1 Announce Type: new Abstract: Federal agencies are deploying large language models (LLMs) to categorize public comment corpora, where the model's organization of the record shapes wh

YoCausal: How Far is Video Generation from World Model? A Causality Perspective

arXiv:2605.30346v1 Announce Type: new Abstract: As video diffusion models (VDMs) advance toward world models, a key question arises: do they truly understand causality, or merely overfit to statistica

Argument Quality Assessment with Large Language Models: A Pairwise Bradley-Terry Approach

arXiv:2605.28313v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in tasks related to reasoning and judgment. However, assessing the quality of arg

Assessing Factual Music Comprehension in Large Audio Language Models

arXiv:2511.05550v2 Announce Type: replace-cross Abstract: Large audio language models (LALMs) leverage multimodal representations to generate open-ended answers to natural language queries about audio

Benchmarking Ultrasound Foundation Models for Fetal Plane Classification

arXiv:2605.27796v1 Announce Type: cross Abstract: Ultrasound is widely used in obstetric care due to its safety, accessibility, and real-time imaging. However, interpretation remains operator-dependen

BlazeEdit: Generalist Image Editing on Mobile Devices with Image-to-Image Diffusion Models

arXiv:2605.28067v1 Announce Type: new Abstract: The remarkable generation quality of modern diffusion models often comes at the cost of massive parameter counts, which necessitate server-side inferenc

Can Decision Trees Teach Large Language Models? Distilling Verbalized Knowledge for Molecular Property Prediction

arXiv:2603.12344v2 Announce Type: replace Abstract: Molecular Property Prediction (MPP) is a fundamental problem in drug discovery that has recently attracted growing attention. Large Language Models

CFDTwin: An open-source GUI and Python toolkit for POD-NN surrogate modeling of ANSYS Fluent simulations

arXiv:2605.27725v1 Announce Type: cross Abstract: High-fidelity computational fluid dynamics (CFD) is widely used for thermal-fluid design, but repeated CFD solves remain expensive for design optimiza

Compositional Generalization in Autoregressive Models via Logit Composition

arXiv:2605.28304v1 Announce Type: new Abstract: Composing autoregressive models remains a core challenge in understanding how large language models can combine behaviors or skills learned across tasks

Do Clinical Models Change Treatment Decisions?

arXiv:2605.28129v1 Announce Type: new Abstract: Clinical foundation models are evaluated with factual or exam-style medical QA, but treatment decisions must change when patient context changes. We int

Entropy-aware Masking for Masked Language Modeling

arXiv:2605.28526v1 Announce Type: new Abstract: Masked language modeling has become a standard pretraining objective for training encoder-based language models. In this approach, certain tokens in the

FLORO: A Multimodal Geospatial Foundation Model for Ecological Remote Sensing Across Sensors and Scales

arXiv:2605.28174v1 Announce Type: cross Abstract: Foundation models offer a promising route to transferable remote sensing representations, but many current approaches depend on very large pretraining

Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players

arXiv:2605.28816v1 Announce Type: new Abstract: World models for interactive video generation have largely focused on single-agent settings, where future observations are generated from a single contr

Local MDI+: Local Feature Importances for Tree-Based Models

arXiv:2506.08928v2 Announce Type: replace Abstract: Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and comp

Nano Banana 2 and Nano Banana Pro are generally available, and already powering creative workflows

model-releasesgoogle-cloud-ai

Organizations are unlocking entirely new ways to use image generation and editing across their industries. To drive next-generation experiences, businesses are embedding AI directly into creative, age

📢Qwen3.7-Max just hit #3 on ITbench-AA — a fresh benchmark testing how well models handle real-world enterprise IT tasks, agentic-style. 🔧…

📢Qwen3.7-Max just hit #3 on ITbench-AA — a fresh benchmark testing how well models handle real-world enterprise IT tasks, agentic-style. 🔧Agentic era, go with Qwen.🏃🏃 Artificial Analysis and IBM Resea

model-releasesqwen--x

Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales

arXiv:2605.28036v1 Announce Type: new Abstract: Diffusion models steer conditional generation with a tunable guidance scale to trade off prompt alignment and diversity. However, existing debiasing tec

We're releasing Paris 2.0, which, to our knowledge, is the world's first decentralized trained video generation model. We benchmarked it aga…

model-releasesclem-delangue--x

We're releasing Paris 2.0, which, to our knowledge, is the world's first decentralized trained video generation model. We benchmarked it against a monolithic model trained on the same data and compute

A closer look at what we released today 🧵 ESMC is a language model trained on billions of protein sequences spanning the full diversity of …

model-releasesyann-lecun--x

A closer look at what we released today 🧵 ESMC is a language model trained on billions of protein sequences spanning the full diversity of life. Trained across 2.8 billion sequences, the model is expo

Advancing Creative Physical Intelligence in Large Multimodal Models

arXiv:2605.26396v1 Announce Type: new Abstract: Large multimodal models (LMMs) have rapidly advanced in perception and reasoning; however, it remains unclear whether these capabilities generalize to d

Safety

Auditing and Fixing Economic Validity in Tabular Foundation Models for Discrete Choice

arXiv:2605.26559v1 Announce Type: cross Abstract: Tabular foundation models achieve strong accuracy on choice prediction tasks, but their predictions often violate the economic logic those tasks requi

safetyarxiv-cs-ai

Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting

arXiv:2605.26562v1 Announce Type: new Abstract: While previous research in multivariate time series forecasting has focused on developing complex holistic models, this work advocates for a shift towar

CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning

arXiv:2502.03946v5 Announce Type: replace Abstract: Data preprocessing is often paid little attention in machine learning, despite its potentially significant impact on model performance. While automa

Continual Model-Based Reinforcement Learning with Hypernetworks

arXiv:2009.11997v3 Announce Type: replace-cross Abstract: Effective planning in model-based reinforcement learning (MBRL) and model-predictive control (MPC) relies on the accuracy of the learned dynam