Search: “models”

Sub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction

arXiv:2606.22606v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong relation extraction (RE), but their computational demands and reliance on proprietary APIs limit deploymen

23 Jun 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

DGX agent

arXiv:2511.22699v4 Announce Type: replace Abstract: The landscape of high-performance image generation models is currently dominated by proprietary systems, such as Nano Banana Pro and Seedream 4.0. L

model-releasesarxiv-cs-cv

23 Jun 2026

Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering

arXiv:2606.11386v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) enable seamless speech interaction by allowing models to listen and speak simultaneously, yet the interna

11 Jun 2026

Quantifying Subliminal Behavioral Transfer Ratios in Language Model Distillation

arXiv:2606.11270v1 Announce Type: cross Abstract: Distillation of a language model intended to transfer benign behavior to a student model may also transfer undesirable characteristics, if they are pr

11 Jun 2026

Domain Adapted Large Language Models for Additive Manufacturing

arXiv:2603.22017v2 Announce Type: replace Abstract: This work presents a collection of multi-modal domain adapted large language models built upon the instruction tuned variants of open weight models

One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability

arXiv:2606.09936v1 Announce Type: cross Abstract: World models are now built on substantially different computational substrates. Latent recurrent state-space models such as PlaNet and the Dreamer fam

PhantomBench: Benchmarking the Non-existential Threat of Language Models

arXiv:2606.11105v1 Announce Type: cross Abstract: Hallucinations, where language models (LMs) generate factually ungrounded responses, pose serious risks, as users tend to blindly rely on them. This i

When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff

arXiv:2606.09932v1 Announce Type: cross Abstract: Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) has become a standard pipeline for Large Language Model (LLM) post-training. SFT

DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Driving

arXiv:2606.08525v1 Announce Type: new Abstract: Reward models play a pivotal role in reinforcement learning (RL) and multi-modal trajectory selection for autonomous driving. However, acquiring such re

9 Jun 2026

NutriMLLM: Multimodal Large Language Models for Dietary Micronutrient Analysis

arXiv:2606.08948v1 Announce Type: cross Abstract: Comprehensive estimation of dietary micronutrients from food images could improve clinical nutrition care, but training such models requires large mul

9 Jun 2026

Applications

Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems

arXiv:2603.24963v3 Announce Type: replace Abstract: Modern computational advertising platforms typically rely on recommendation systems to predict user responses, such as click-through rates, conversi

applicationsarxiv-cs-ai

8 Jun 2026

Machine Learning for Electron-Scale Turbulence Modeling in W7-X

arXiv:2511.04567v2 Announce Type: replace-cross Abstract: Constructing reduced models for turbulent transport is essential for accelerating profile predictions and enabling many-query tasks such as pa

8 Jun 2026

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View

arXiv:2509.25522v3 Announce Type: replace Abstract: Recent advancements in generative models have allowed the emergence of a promising paradigm for recommender systems (RS), known as Generative Recomm

8 Jun 2026

Dream.exe: Can Video Generation Models Dream Executable Robot Manipulation?

arXiv:2606.04811v1 Announce Type: new Abstract: Video generation models have made impressive strides in synthesizing visually compelling content, yet their outputs remain confined to the virtual domai

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

arXiv:2606.05015v1 Announce Type: new Abstract: World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet h

safetyarxiv-cs-ro

Geometry-Aware Hallucination Detection in Large Language Models

arXiv:2601.06196v3 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate factually incorrect or unsupported content, commonly referred to as hallucinations. Prior wor

Semiparametric Preference Optimization: Your Language Model is Secretly a Single-Index Model

arXiv:2512.21917v3 Announce Type: replace-cross Abstract: Policy alignment to preference data typically assumes a known link function between observed preferences and latent rewards (e.g., Bradley-Ter

safetyarxiv-cs-ai

Token Rankings are Unforgeable Language Model Signatures

arXiv:2606.04459v1 Announce Type: cross Abstract: Language model parameters are known to impose unique (to each model) geometric constraints on their logit outputs, which serves as a signature that id

UniCanvas: A Diffusion-base Unified Model for Text-in-Image Joint Generation

arXiv:2606.04264v1 Announce Type: new Abstract: Recent years have seen remarkable progress in unified vision-language models handling both multimodal understanding and generation within a single archi

researcharxiv-cs-cv

ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning

arXiv:2606.02802v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model struct

3 Jun 2026

Hybrid Dynamics Modeling for a Flexible 2-DoF Robotic Arm

model-releasesarxiv-cs-ro

arXiv:2606.02969v1 Announce Type: new Abstract: This paper examines three approaches for modeling the dynamics of a flexible-link 2-DoF robotic arm to address unmodeled dynamics not captured by rigid-

3 Jun 2026

Large Byte Model: Teaching Language Models About Compiled Code

arXiv:2606.02834v1 Announce Type: cross Abstract: Malware analysis starts with the raw bytes of an executable program, and tools to 'lift' these to higher-level representations, such as assembly, are

3 Jun 2026

3DCodeBench: Benchmarking Agentic Procedural 3D Modeling Via Code

arXiv:2606.01057v1 Announce Type: cross Abstract: Procedural 3D modeling through code is emerging as a versatile paradigm, offering deterministic, engine-ready, and precisely editable assets that neur

Large Electron Model: A Universal Ground State Predictor

arXiv:2603.02346v2 Announce Type: replace-cross Abstract: We introduce Large Electron Model, a single neural network model that produces variational wavefunctions of interacting electrons over the ent

LL-Bench: Rethinking Low-Level Vision Evaluation in the Era of Large-Scale Generative Models

arXiv:2606.02535v1 Announce Type: new Abstract: Large-scale generative models have demonstrated remarkable capabilities across image generation and editing tasks. However, their performance in low-lev

On the Generalization Gap in Self-Evolving Language Model Reasoning

model-releasesarxiv-cs-cl

arXiv:2606.01075v1 Announce Type: new Abstract: Recent work suggests that large language models (LLMs) can improve through self-evolution (SE), using supervision signals generated by the model itself.

Saliency-Aware Model Merging

arXiv:2606.00511v1 Announce Type: cross Abstract: Model merging aims to consolidate multiple task-specific models fine-tuned on different datasets into a unified architecture that performs cross-domai

Same Payload, Different Channel: Measuring Trust Asymmetry in Tool-Using Language Models

model-releasesarxiv-cs-cl

arXiv:2606.00566v1 Announce Type: cross Abstract: As language models take on agentic roles that span calling external APIs, reading tool outputs, and acting on instructions embedded in third-party con

Scaling depth capacity via zero/one-layer model expansion

arXiv:2511.04981v2 Announce Type: replace Abstract: Model depth is a double-edged sword in deep learning: deeper models achieve higher accuracy but require higher computational cost. To efficiently tr

researcharxiv-cs-lg

Agents

VLAMotor: Test-Guided Enhancement of Vision-Language-Action Models via Agent-BasedData Synthesis

arXiv:2606.00053v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models follow a data-driven paradigm and are constrained by the coverage of training data, making them prone to failure on

agentsarxiv-cs-ro

How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science

arXiv:2602.09309v2 Announce Type: replace-cross Abstract: Every generative model for crystalline materials harbors a critical structure size beyond which its outputs become unreliable; we call this th

1 Jun 2026

Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts

arXiv:2605.30184v1 Announce Type: new Abstract: While AI weather models excel at short-to-medium range forecasts (up to 15 days), they frequently suffer from ill-defined 'instabilities' when rolled ou

29 May 2026

GPF-LiveNews: A Streaming Evaluation Protocol for Group-Conditioned Framing in Large Language Models

arXiv:2605.28848v1 Announce Type: cross Abstract: Deployed language models are evaluated in a non-stationary environment: model versions, retrieval layers, safety systems, and real-world inputs all ch

29 May 2026

Latent Performance Profiling of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.30018v1 Announce Type: new Abstract: Large language models (LLMs) frequently achieve impressive scores on standardized benchmarks, yet accuracy alone offers a limited view of their capabili

29 May 2026

Applications

A Sheaf-Theoretic and Topological Perspective on Complex Network Modeling and Attention Mechanisms in Graph Neural Models

arXiv:2601.21207v3 Announce Type: replace-cross Abstract: Combinatorial and topological structures, such as graphs, simplicial complexes, and cell complexes, form the foundation of geometric and topol

applicationsarxiv-cs-ai

Accelerating Reinforcement Learning Training Using Simulation Surrogate Models

arXiv:2605.27556v1 Announce Type: cross Abstract: High-fidelity simulation models are widely used to analyze complex stochastic systems, but their high computational cost motivates the development of

researcharxiv-cs-lg

Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting

arXiv:2509.23074v3 Announce Type: replace-cross Abstract: In the era of increasingly complex AI models for time series forecasting, progress is often measured by marginal improvements on benchmark lea

DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving

arXiv:2605.28544v1 Announce Type: new Abstract: Pretrained foundation models have become an important basis for end-to-end autonomous driving. In contrast to vision-language models pretrained primaril

Models That Know How Evaluations Are Designed Score Safer

arXiv:2605.28591v1 Announce Type: cross Abstract: The validity of AI safety evaluations depends on models behaving consistently across controlled and deployment settings. Prior work has identified tes

CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection

arXiv:2605.26294v1 Announce Type: new Abstract: Skin cancer is a common and fast rising malignancy worldwide. Early detection is critical for improving outcomes. Deep learning models trained on dermos

27 May 2026

MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths

arXiv:2510.08932v2 Announce Type: replace Abstract: Recently, a growing body of research has focused on either optimizing CTR model architectures to better model feature interactions or refining train

27 May 2026

'PhyWorldBench': A Comprehensive Evaluation of Physical Realism in Text-to-Video Models

arXiv:2507.13428v3 Announce Type: replace-cross Abstract: Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurate

27 May 2026

A computational phase transition for learning-to-sample from Ising models

arXiv:2605.24752v1 Announce Type: new Abstract: We study learning-to-sample -- a basic algorithmic task underlying generative modeling -- for Ising models, a standard testbed for algorithmic ideas in

From Simulation to Enaction: Post-trained language models recognize and react to their own generations

arXiv:2605.25459v1 Announce Type: cross Abstract: Language models are pretrained as passive predictors with no incentive to model the consequences of their own outputs. Post-training changes this: a m

safetyarxiv-cs-ai

JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures

arXiv:2602.17162v2 Announce Type: replace Abstract: Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the 'Laws of Nature'. Whil

JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data

arXiv:2605.24414v1 Announce Type: new Abstract: We introduce JT-Safe-V2, a large language model designed to advance the safety and trustworthiness of foundation models, extending our previous JT-Safe

safetyarxiv-cs-ai

LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

model-releasesarxiv-cs-ro

arXiv:2510.03827v2 Announce Type: replace-cross Abstract: LIBERO has emerged as a widely adopted benchmark for evaluating Vision-Language-Action (VLA) models; however, its current training and evaluat

Second Guess: Detecting Uncertainty Through Abstention and Answer Stability in Small Language Models

arXiv:2605.25394v1 Announce Type: new Abstract: Large language models often generate confident but incorrect answers rather than abstaining when uncertain. This problem is particularly acute for small