Search: “models”

TeachObs: A Human-Validated Benchmark for Multimodal Teaching Observation and Model Evaluation

arXiv:2605.30673v1 Announce Type: new Abstract: Classroom videos contain observable teaching practices, but their pedagogical and visual signals are rarely organized in forms suitable for model evalua

1 Jun 2026

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Adaptive Targeted Dynamic Chunking for Tokenization-Free Hierarchical Model

DGX agent

arXiv:2605.30080v1 Announce Type: new Abstract: Tokenization-free hierarchical models are emerging as a promising alternative to traditional Large Language Models (LLMs), addressing inherent preproces

researcharxiv-cs-cl

29 May 2026

Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements

arXiv:2510.27663v3 Announce Type: replace-cross Abstract: Modern imaging techniques heavily rely on Bayesian statistical models to address difficult image reconstruction and restoration tasks. This pa

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting

arXiv:2510.02480v3 Announce Type: replace Abstract: Large language models (LLMs) can be influenced by harmful or irrelevant context, which can significantly harm model performance on downstream tasks.

researcharxiv-cs-ai

Embodied3DBench: Benchmarking Low-Level Embodied Spatial Intelligence of Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2605.29074v1 Announce Type: new Abstract: Are current Vision Language Models (VLMs) ready to comprehend and reason about complex embodied interactions in 3D environments? We introduce Embodied3D

MATNet: Multi-Level Fusion Transformer-Based Model for Day-Ahead PV Generation Forecasting

arXiv:2306.10356v3 Announce Type: replace-cross Abstract: Accurate forecasting of renewable generation is crucial to facilitate the integration of Renewable Energy Sources into the power system. Focus

MELD: Mel-Spectrogram-Based Speech Language Modeling with Discrete Latent Variables

arXiv:2605.29859v1 Announce Type: cross Abstract: Recent speech language models rely on encoders that are optimized separately from autoregressive models. Since these encoders are unaware of the downs

researcharxiv-cs-cl

MENTOR: Efficient Multimodal-Conditioned Tuning for Autoregressive Vision Generation Models

arXiv:2507.09574v3 Announce Type: replace-cross Abstract: Recent text-to-image models produce high-quality results but still struggle with precise visual control, balancing multimodal inputs, and requ

Rethinking Stepwise Model Routing: A Cost-Efficient Table Reasoning Perspective

arXiv:2605.29319v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on table reasoning tasks but incur substantial inference cost due to long reasoning traces. Ste

researcharxiv-cs-cl

The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure

arXiv:2605.29087v1 Announce Type: new Abstract: Reasoning models are evaluated on single-turn benchmarks but deployed in multi-turn dialogue, where users push back on correct answers. Under sustained

UA-Legal-Bench: A Benchmark for Evaluating Large Language Models on Ukrainian Legal Reasoning

arXiv:2605.29170v1 Announce Type: cross Abstract: Legal NLP benchmarks are overwhelmingly English-centric, leaving failure modes in morphologically rich, non-Latin-script languages undetected. We intr

VLAConf: Calibrated Task-Success Confidence for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2605.29605v1 Announce Type: new Abstract: Confidence estimation for Vision-Language-Action (VLA) models is essential for robots to perform manipulation tasks in the open world, providing crucial

A Methodology to Assess Power Modeling in Energy-Aware Federated Learning on Heterogeneous Mobile Devices

arXiv:2605.27601v1 Announce Type: cross Abstract: Estimating CPU power on heterogeneous ARM-based commodity devices is challenging due to limited access to CPU's voltage domains. As a result, state-of

Tutorials

Continuous Diffusion Models Can Obey Formal Syntax

arXiv:2602.12468v2 Announce Type: replace Abstract: Diffusion language models offer a promising alternative to autoregressive models due to their global, non-causal generation process, but their conti

tutorialsarxiv-cs-lg

Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models

arXiv:2512.00349v2 Announce Type: replace Abstract: Are frontier AI systems becoming more capable? Certainly. Yet such progress is not an unalloyed blessing but rather a Trojan horse: behind their per

Dynamic Topic Modeling with a Higher-Order Hypergraphical Representation

arXiv:2605.28269v1 Announce Type: new Abstract: Dynamic topic modeling is widely used to analyze evolving trends in scientific literature, medical records, and social media. Traditional topic models r

Agents

Faster Thermal Profiling of a Lunar Rover with Machine Learning Adapted Finite Difference Model

arXiv:2605.27651v1 Announce Type: new Abstract: Autonomous space systems operating in extreme thermal environments require accurate and efficient thermal modeling to support both pre-mission system de

agentsarxiv-cs-lg

Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models

arXiv:2510.17620v2 Announce Type: replace Abstract: Large language models may encode sensitive information or outdated knowledge that needs to be removed, to ensure responsible and compliant model res

researcharxiv-cs-cl

Harness-Bench: Measuring Harness Effects across Models in Realistic Agent Workflows

arXiv:2605.27922v1 Announce Type: new Abstract: LLM agents are increasingly deployed as executable systems that use tools, modify workspaces, and produce concrete artifacts. In such workflows, perform

NUCLEUS-MoE: Unified Model of Pool Boiling for Liquid Cooling

arXiv:2605.27722v1 Announce Type: new Abstract: Two-phase boiling enables heat transfer rates an order of magnitude higher than single-phase cooling, but it remains difficult to model due to the stron

Parameter-Efficient Generative Modeling with Controlled Vector Fields

model-releasesarxiv-cs-lg

arXiv:2605.28267v1 Announce Type: new Abstract: We introduce a continuous-time generative modeling framework, motivated by the Chow-Rashevskii theorem, that builds expressive flows from a small set of

Probing for Knowledge Attribution in Large Language Models

arXiv:2602.22787v2 Announce Type: replace-cross Abstract: Large language model (LLM) hallucinations, meaning fluent but factually incorrect generations, fall into two types: faithfulness violations, w

Prompting Is All You Need: Multi-view Prompting Large Language Models for Aspect-Based Sentiment Analysis

arXiv:2605.28058v1 Announce Type: new Abstract: Recent work explored the capabilities of Large Language Models (LLMs) in Aspect-Based Sentiment Analysis (ABSA) through few-shot prompting, requiring su

Local Ai

Sentence Curve Language Models

arXiv:2602.01807v3 Announce Type: replace Abstract: Language models (LMs) are a central component of modern AI systems, and diffusion language models (DLMs) have recently emerged as a competitive alte

local-aiarxiv-cs-cl

Turning Video Models into Generalist Robot Policies

arXiv:2605.27817v1 Announce Type: cross Abstract: Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across

Tutorials

Why Gaussian Diffusion Models Fail on Discrete Data and How to Prevent It?

arXiv:2604.02028v2 Announce Type: replace Abstract: Diffusion models have become a standard approach for generative modeling in continuous domains, yet their application to discrete data remains chall

tutorialsarxiv-cs-cl

From Scores to Gibbs Correctors: Accelerating Uniform-Rate Discrete Diffusion Models

arXiv:2605.27352v1 Announce Type: new Abstract: Discrete diffusion models have achieved strong empirical performance in text and other symbolic domains, but, especially for uniform-rate models, they o

Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini

model-releasesarxiv-cs-cv

arXiv:2605.27295v1 Announce Type: new Abstract: We introduce Gemini Embedding 2, a native multimodal embedding model that allows embedding video, audio, image, and text modalities in a unified represe

KARMA: Karma-Aligned Reward Model Adaptation

arXiv:2605.26738v1 Announce Type: new Abstract: Human communication depends on implicit social signals where effectiveness is shaped by tone, context, and conversational norms rather than semantic con

safetyarxiv-cs-cl

Large Language Model-Powered Query-Driven Event Timeline Summarization in Industrial Search

arXiv:2605.27066v1 Announce Type: new Abstract: Understanding how events evolve over time is essential for search engines handling queries about trending news. We present QDET (Query-Driven Event Time

Learning When to Think While Listening in Large Audio-Language Models

arXiv:2605.27190v1 Announce Type: cross Abstract: Recent advances in Large Audio-Language Models (LALMs) have made real-time, streaming spoken interaction increasingly practical. In this setting, reas

LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations?

arXiv:2605.26781v1 Announce Type: new Abstract: Advanced Large Multimodal Models (LMMs) have demonstrated impressive performance in K-12 reasoning tasks, exhibiting great promise as intelligent tutors

Negligible in Size, Significant in Effect: On Scale Vectors in Large Language Models

arXiv:2605.26895v1 Announce Type: cross Abstract: Normalization layers in modern large language models (LLMs) consist of a deterministic normalization operation and a learnable scale vector. While the

Reasoning, Code, or Both? How Large Language Models Handle Variations in Math Questions

arXiv:2605.26414v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve impressive accuracy on mathematical reasoning benchmarks, yet their performance drops when problems are modified wi

A Closer Look on Memorization in Tabular Diffusion Model: A Data-Centric Perspective

arXiv:2505.22322v3 Announce Type: replace Abstract: Diffusion models have shown strong performance in generating high-quality tabular data, but they carry privacy risks by reproducing exact training s

A comparative study of accuracy and rollout stability of temporal surrogate models

arXiv:2605.24868v1 Announce Type: new Abstract: Temporal surrogate models are effective for predicting chaotic dynamical systems where computational cost can be prohibitive. Several deep neural networ

safetyarxiv-cs-lg

Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text

arXiv:2605.24546v1 Announce Type: new Abstract: Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task trad

researcharxiv-cs-ai

Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models

arXiv:2605.25765v1 Announce Type: cross Abstract: Concept unlearning aims to erase a target concept from a pretrained text-to-image diffusion model without retraining. Closed-form methods are attracti

CyberMaskQA: A Privacy-Aware Benchmark for Evaluating Large Language Models in Cybersecurity Question Answering

model-releasesarxiv-cs-lg

arXiv:2605.24765v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly applied to cybersecurity question answering (QA) for critical tasks such as incident response and vulner

Do Understanding and Generation Fight? A Diagnostic Study of DPO for Unified Multimodal Models

arXiv:2603.17044v2 Announce Type: replace-cross Abstract: Unified multimodal models share a language model backbone for both understanding and generating images. Can DPO align both capabilities simult

Agents

Drift-Resistant Navigation World Model with Anchored Epipolar Guidance

arXiv:2605.24761v1 Announce Type: cross Abstract: We propose Drift-Resistant Navigation World Model, a generative model that mitigates both perceptual drift and geometric drift in conventional rollout

agentsarxiv-cs-ro

FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model

arXiv:2510.10921v3 Announce Type: replace-cross Abstract: Fine-grained vision-language understanding requires precise alignment between visual content and linguistic descriptions, a capability that re

Generative Visual Code Mobile World Models

arXiv:2602.01576v2 Announce Type: replace-cross Abstract: Mobile Graphical User Interface (GUI) World Models (WMs) offer a promising path for improving mobile GUI agent performance at train- and infer

MARS: Margin and Semantic-Aware Data Augmentation for Reward Modeling

arXiv:2602.17658v2 Announce Type: replace-cross Abstract: Reward modeling is central to alignment pipelines such as RLHF, RLAIF, and PPO-based policy optimization, yet its reliability is constrained b

Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs

arXiv:2605.24681v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown great promise in multilingual machine translation (MT), even with limited bilingual supervision. However, fine

Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning

arXiv:2605.25210v1 Announce Type: cross Abstract: Diffusion models are increasingly used as powerful conditional generators, yet real deployments often involve multiple target distributions arising fr

ScaleAcross Explorer: Exploring Communication Optimization for Scale-Across AI Model Training

arXiv:2605.24326v1 Announce Type: cross Abstract: The rapid scaling of large language model training requires distributing GPU resources across multiple data center buildings and regions. We refer to

The Age of Curiosity Meets the Age of AI: Benchmarking Child Safety in Large Language Models

arXiv:2605.25510v1 Announce Type: new Abstract: Children increasingly have access to Large Language Models (LLMs), which may expose them to responses that are developmentally inappropriate or require