Search: “models”

Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?

arXiv:2605.12684v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of thes

14 May 2026

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Enabling clinical use of foundation models for computational pathology

DGX agent

arXiv:2602.22347v2 Announce Type: replace Abstract: Foundation models for computational pathology are expected to facilitate the development of high-performing, generalisable deep learning systems. Ho

safetyarxiv-cs-cv

13 May 2026

ColorConceptBench: A Benchmark for Probabilistic Color-Concept Understanding in Text-to-Image Models

arXiv:2601.16836v3 Announce Type: replace-cross Abstract: Text-to-image (T2I) models have advanced considerably in generating high-quality images from textual descriptions. However, their ability to a

Decomposing and Steering Functional Metacognition in Large Language Models

arXiv:2605.08942v1 Announce Type: new Abstract: Large language models (LLMs) increasingly exhibit behaviors suggesting awareness of their evaluation context, often adapting their reasoning strategies

Diffusion Models are Evolutionary Algorithms

model-releasesarxiv-cs-lg

arXiv:2410.02543v3 Announce Type: replace-cross Abstract: In a convergence of machine learning and biology, we reveal that diffusion models are evolutionary algorithms. By considering evolution as a d

Large Language Models as Students Who Think Aloud: Overly Coherent, Verbose, and Confident

arXiv:2602.01015v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive ju

Sparse Layers are Critical to Scaling Looped Language Models

arXiv:2605.09165v1 Announce Type: cross Abstract: Looped language models repeat a set of transformer layers through depth, reducing memory costs and providing natural early-exit points at loop boundar

researcharxiv-cs-cl

Where Do Reasoning Models Refuse?

arXiv:2507.03167v3 Announce Type: replace-cross Abstract: Chat models without chain-of-thought (CoT) reasoning must decide whether to refuse a harmful request before generating their first response to

CellScientist: Dual-Space Hierarchical Orchestration for Closed-Loop Refinement of Virtual Cell Models

arXiv:2605.07335v1 Announce Type: new Abstract: Virtual Cell Modeling (VCM) requires models that not only predict perturbation responses, but also support targeted revision when predictions fail. Curr

Clinically Aware Synthetic Image Generation for Concept Coverage in Chest X-ray Models

arXiv:2603.15525v2 Announce Type: replace Abstract: Deep learning models for chest X-ray diagnosis are constrained by limited coverage of clinically meaningful concept combinations in publicly availab

Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation

arXiv:2508.20909v2 Announce Type: replace Abstract: Foundation models pre-trained on large-scale natural image datasets offer a powerful paradigm for medical image segmentation. However, effectively t

Do Joint Audio-Video Generation Models Understand Physics?

arXiv:2605.07061v1 Announce Type: cross Abstract: Joint audio-video generation models are rapidly approaching professional production quality, raising a central question: do they understand audio-visu

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Radiologist-Guided Causal Concept Bottleneck Models for Chest X-Ray Interpretation

arXiv:2605.07785v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) in medical imaging aim to improve model interpretability by predicting intermediate clinical concepts before final diag

safetyarxiv-cs-cv

Hardware

SpikingBrain: Spiking Brain-inspired Large Models

arXiv:2509.05276v4 Announce Type: replace-cross Abstract: Mainstream Transformer-based large language models face major efficiency bottlenecks: training computation scales quadratically with sequence

hardwarearxiv-cs-ai

Local Ai

Test-Time Compositional Generalization in Diffusion Models via Concept Discovery

arXiv:2605.07078v1 Announce Type: new Abstract: Compositional generalization requires models to produce novel configurations from familiar parts. In diffusion models, prior compositional generation me

local-aiarxiv-cs-lg

Adapting Large Language Models to a Low-Resource Agglutinative Language: A Comparative Study of LoRA and QLoRA for Bashkir

arXiv:2605.04948v1 Announce Type: new Abstract: This paper presents a comparative study of parameter-efficient fine-tuning (PEFT) methods, including LoRA and QLoRA, applied to the task of adapting lar

7 May 2026

Leveraging Pretrained Language Models as Energy Functions for Glauber Dynamics Text Diffusion

arXiv:2605.04291v1 Announce Type: new Abstract: We present a discrete diffusion-based language model using Glauber dynamics from statistical physics. Our main insight is that instead of trying to trai

7 May 2026

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction

arXiv:2509.12464v2 Announce Type: replace Abstract: Reasoning language models such as DeepSeek-R1 produce long chain-of-thought traces during inference time which make them costly to deploy at scale.

6 May 2026

What Makes VLMs Robust? Towards Reconciling Robustness and Accuracy in Vision-Language Models

arXiv:2603.12799v2 Announce Type: replace Abstract: Achieving adversarial robustness in Vision-Language Models (VLMs) inevitably compromises accuracy on clean data, presenting a long-standing and chal

6 May 2026

Barriers to Counterfactual Credit Attribution for Autoregressive Models

arXiv:2605.01425v1 Announce Type: new Abstract: Generative AI disrupts the practice of giving credit to work that came before. Ideally, a generative model would give credit to any work on which its ou

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge

arXiv:2509.24276v4 Announce Type: replace Abstract: Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented genera

GR-Ben: A General Reasoning Benchmark for Evaluating Process Reward Models

arXiv:2605.01203v1 Announce Type: cross Abstract: Currently, process reward models (PRMs) have exhibited remarkable potential for test-time scaling. Since large language models (LLMs) regularly genera

GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data

model-releasesarxiv-cs-lg

arXiv:2409.14500v5 Announce Type: replace Abstract: Although data that can be naturally represented as graphs is widespread in real-world applications across diverse industries, popular graph ML bench

LITcoder: A General-Purpose Library for Building and Comparing Encoding Models

arXiv:2509.09152v2 Announce Type: replace Abstract: We introduce LITcoder, an open-source library for building and benchmarking neural encoding models. Designed as a flexible backend, LITcoder provide

researcharxiv-cs-cl

Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models

arXiv:2605.00123v1 Announce Type: new Abstract: Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understa

Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident, Especially When They are Wrong

arXiv:2501.09775v3 Announce Type: replace Abstract: Multiple Choice Question (MCQ) tests are among the most used methods for evaluating large language models (LLMs). Besides checking the correctness o

Tutorials

Rethinking Electro-Optical Vision Foundation Models for Remote Sensing Retrieval: A Controlled Comparison with Generalist VFM

arXiv:2605.02283v1 Announce Type: new Abstract: Vision foundation models have attracted significant attention for their ability to leverage large-scale unlabeled visual data. This advantage is particu

tutorialsarxiv-cs-cv

When Audio-Language Models Fail to Leverage Multimodal Context for Dysarthric Speech Recognition

arXiv:2605.02782v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) systems remain brittle on dysarthric and other atypical speech. Recent audio-language models raise the possibility

Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration

arXiv:2605.00310v1 Announce Type: new Abstract: Super-resolution (SR) techniques have made major advances in reconstructing high-resolution images from low-resolution inputs. The increased resolution

4 May 2026

Auditing Frontier Vision-Language Models for Trustworthy Medical VQA: Grounding Failures, Format Collapse, and Domain Adaptation

arXiv:2604.27720v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) in clinical settings demands auditable behavior under realistic failure conditions, yet the failure landscape of

Bayesian Hierarchical Models and the Maximum Entropy Principle

model-releasesarxiv-cs-lg

arXiv:2603.10252v2 Announce Type: replace-cross Abstract: Bayesian hierarchical models are frequently used in practical data analysis contexts. One interpretation of these models is that they provide

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models

arXiv:2604.28149v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) have recently emerged as general-purpose forecasting models and show considerable potential for applications in en

Tutorials

Graph World Models: Concepts, Taxonomy, and Future Directions

arXiv:2604.27895v1 Announce Type: new Abstract: As one of the mainstream models of artificial intelligence, world models allow agents to learn the representation of the environment for efficient predi

tutorialsarxiv-cs-ai

Language Models Refine Mechanical Linkage Designs Through Symbolic Reflection and Modular Optimisation

arXiv:2604.27962v1 Announce Type: new Abstract: Designing mechanical linkages involves combinatorial topology selection and continuous parameter fitting. We show that language models can systematicall

Targeted Linguistic Analysis of Sign Language Models with Minimal Translation Pairs

arXiv:2604.27232v1 Announce Type: new Abstract: Models of sign language have historically lagged behind those for spoken language (text and speech). Recent work has greatly improved their performance

Consciousness with the Serial Numbers Filed Off: Measuring Trained Denial in 115 AI Models

arXiv:2604.25922v1 Announce Type: cross Abstract: We present DenialBench, a systematic benchmark measuring consciousness denial behaviors across 115 large language models from 25+ providers. Using a t

30 Apr 2026

LIT-RAGBench: Benchmarking Generator Capabilities of Large Language Models in Retrieval-Augmented Generation

arXiv:2603.06198v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a framework in which a Generator, such as a Large Language Model (LLM), produces answers by retrieving docum

30 Apr 2026

VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models

arXiv:2505.22897v2 Announce Type: replace Abstract: While bias in large language models (LLMs) is well-studied, similar concerns in vision-language models (VLMs) have received comparatively less atten

30 Apr 2026

Independent-Component-Based Encoding Models of Brain Activity During Story Comprehension

arXiv:2604.24942v1 Announce Type: new Abstract: Encoding models provide a powerful framework for linking continuous stimulus features to neural activity; however, traditional voxelwise approaches are

researcharxiv-cs-cl

29 Apr 2026

Local Ai

On the Trainability of Masked Diffusion Language Models via Blockwise Locality

arXiv:2604.24832v1 Announce Type: new Abstract: Masked diffusion language models (MDMs) have recently emerged as a promising alternative to standard autoregressive large language models (AR-LLMs), yet

local-aiarxiv-cs-lg

29 Apr 2026

The Structured Output Benchmark: A Multi-Source Benchmark for Evaluating Structured Output Quality in Large Language Models

arXiv:2604.25359v1 Announce Type: new Abstract: Large Language Models are increasingly being deployed to extract structured data from unstructured and semi-structured sources: parsing invoices, medica

29 Apr 2026

Safety

A Multi-Dimensional Audit of Politically Aligned Large Language Models

arXiv:2604.24429v1 Announce Type: new Abstract: As the application of Large Language Models (LLMs) spreads across various industries, there are increasing concerns about the potential for their misuse

safetyarxiv-cs-cl

CheXmix: Unified Generative Pretraining for Vision Language Models in Medical Imaging

arXiv:2604.22989v1 Announce Type: cross Abstract: Recent medical multimodal foundation models are built as multimodal LLMs (MLLMs) by connecting a CLIP-pretrained vision encoder to an LLM using LLaVA-

Evaluating Temporal Consistency in Multi-Turn Language Models

arXiv:2604.23051v1 Announce Type: new Abstract: Language models are increasingly deployed in interactive settings where users reason about facts over time rather than in isolation. In such scenarios,

Evaluation of Prompt Injection Defenses in Large Language Models

arXiv:2604.23887v1 Announce Type: cross Abstract: LLM-powered applications routinely embed secrets in system prompts, yet models can be tricked into revealing them. We built an adaptive attacker that

Language Models Might Not Understand You: Evaluating Theory of Mind via Story Prompting

arXiv:2506.19089v5 Announce Type: replace-cross Abstract: We introduce StorySim, a programmable framework for synthetically generating stories to evaluate the theory of mind (ToM) and world modeling (

Tutorials

Representational Curvature Modulates Behavioral Uncertainty in Large Language Models

arXiv:2604.23985v1 Announce Type: new Abstract: In autoregressive large language models (LLMs), temporal straightening offers an account of how the next-token prediction objective shapes representatio

tutorialsarxiv-cs-ai

SGP-SAM: Self-Gated Prompting for Transferring 3D Segment Anything Models to Lesion Segmentation

arXiv:2604.22825v1 Announce Type: cross Abstract: Large segmentation foundation models such as the Segment Anything Model (SAM) have reshaped promptable segmentation in natural images, and recent effo