Search: “models”

vla-eval: A Unified Evaluation Harness for Vision-Language-Action Models

arXiv:2603.13966v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are increasingly evaluated across multiple simulation benchmarks, yet adding each benchmark to an evaluation pip

20 Apr 2026

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Model Releases

AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models

DGX agent

arXiv:2505.10846v3 Announce Type: replace Abstract: This paper presents AutoRAN, the first framework to automate the hijacking of internal safety reasoning in large reasoning models (LRMs). At its cor

model-releasesarxiv-cs-lg

17 Apr 2026

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models

arXiv:2604.14156v1 Announce Type: new Abstract: Large language models deliver strong generative performance but at the cost of massive parameter counts, memory use, and decoding latency. Prior work ha

Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure Generation

arXiv:2604.13354v1 Announce Type: cross Abstract: The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially

researcharxiv-cs-ai

From Black Box to Glass Box: Cross-Model ASR Disagreement to Prioto Review in Ambient AI Scribe Documentation

arXiv:2604.14152v1 Announce Type: cross Abstract: Ambient AI 'scribe' systems promise to reduce clinical documentation burden, but automatic speech recognition (ASR) errors can remain unnoticed withou

applicationsarxiv-cs-cl

POP: Prefill-Only Pruning for Efficient Large Model Inference

arXiv:2602.03295v2 Announce Type: replace Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated remarkable capabilities. However, their deployment is hindered by s

Tutorials

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold

arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy

tutorialsarxiv-cs-ai

Robustness of Vision Foundation Models to Common Perturbations

arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright

researcharxiv-cs-cv

Data-driven Learning of Probabilistic Model of Binary Droplet Collision for Spray Simulation

model-releasesarxiv-cs-lg

arXiv:2604.13594v1 Announce Type: cross Abstract: Binary droplet collisions are ubiquitous in dense sprays. Traditional deterministic models cannot adequately represent transitional and stochastic beh

Gaslight, Gatekeep, V1-V3: Early Visual Cortex Alignment Shields Vision-Language Models from Sycophantic Manipulation

arXiv:2604.13803v1 Announce Type: new Abstract: Vision-language models are increasingly deployed in high-stakes settings, yet their susceptibility to sycophantic manipulation remains poorly understood

Guided Transfer Learning for Discrete Diffusion Models

arXiv:2512.10877v4 Announce Type: replace Abstract: Discrete diffusion models (DMs) have achieved strong performance in language and other discrete domains, offering a compelling alternative to autore

applicationsarxiv-cs-lg

Hardware

Hydra: Unifying Document Retrieval and Generation in a Single Vision-Language Model

arXiv:2603.28554v2 Announce Type: replace Abstract: Visual document understanding typically requires separate retrieval and generation models, doubling memory and system complexity. We present Hydra,

hardwarearxiv-cs-cv

Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models

arXiv:2510.14232v2 Announce Type: replace-cross Abstract: Competitive programming has become a rigorous benchmark for evaluating the reasoning and problem-solving capabilities of large language models

Are Video Reasoning Models Ready to Go Outside?

arXiv:2603.10652v2 Announce Type: replace-cross Abstract: In real-world deployment, vision-language models often encounter disturbances such as weather, occlusion, and camera motion. Under such condit

GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts

arXiv:2604.12978v1 Announce Type: new Abstract: Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cl

MAML-KT: Addressing Cold Start Problem in Knowledge Tracing for New Students via Few-Shot Model-Agnostic Meta Learning

arXiv:2603.00137v2 Announce Type: replace-cross Abstract: Knowledge tracing (KT) models are commonly evaluated by training on early interactions from all students and testing on later responses. While

researcharxiv-cs-ai

On Efficient Variants of Segment Anything Model: A Survey

arXiv:2410.04960v5 Announce Type: replace Abstract: The Segment Anything Model (SAM) is a foundational model for image segmentation tasks, known for its strong generalization across diverse applicatio

applicationsarxiv-cs-cv

PromptEcho: Annotation-Free Reward from Vision-Language Models for Text-to-Image Reinforcement Learning

arXiv:2604.12652v1 Announce Type: cross Abstract: Reinforcement learning (RL) can improve the prompt following capability of text-to-image (T2I) models, yet obtaining high-quality reward signals remai

Reading Between the Pixels: Linking Text-Image Embedding Alignment to Typographic Attack Success on Vision-Language Models

arXiv:2604.12371v1 Announce Type: new Abstract: We study typographic prompt injection attacks on vision-language models (VLMs), where adversarial text is rendered as images to bypass safety mechanisms

Red Teaming Large Reasoning Models

arXiv:2512.00412v4 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) have emerged as a powerful advancement in multi-step reasoning tasks, offering enhanced transparency and logical

Local Ai

RePAIR: Interactive Machine Unlearning through Prompt-Aware Model Repair

arXiv:2604.12820v1 Announce Type: new Abstract: Large language models (LLMs) inherently absorb harmful knowledge, misinformation, and personal data during pretraining on large-scale web corpora, with

local-aiarxiv-cs-ai

T2I-BiasBench: A Multi-Metric Framework for Auditing Demographic and Cultural Bias in Text-to-Image Models

arXiv:2604.12481v1 Announce Type: new Abstract: Text-to-image (T2I) generative models achieve impressive visual fidelity but inherit and amplify demographic imbalances and cultural biases embedded in

When Reasoning Models Hurt Behavioral Simulation: A Solver-Sampler Mismatch in Multi-Agent LLM Negotiation

model-releasesarxiv-cs-lg

arXiv:2604.11840v1 Announce Type: new Abstract: Large language models are increasingly used as agents in social, economic, and policy simulations. A common assumption is that stronger reasoning should

Agents

A collaborative agent with two lightweight synergistic models for autonomous crystal materials research

arXiv:2604.11540v1 Announce Type: new Abstract: Current large language models require hundreds of billions of parameters yet struggle with domain-specific reasoning and tool coordination in materials

agentsarxiv-cs-ai

A Minimal Mathematical Model for Conducting Patterns

model-releasesarxiv-cs-ro

arXiv:2604.10356v1 Announce Type: cross Abstract: We present a minimal mathematical model for conducting patterns that separates geometric trajectory from temporal parametrization. The model is based

Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series

arXiv:2604.10799v1 Announce Type: cross Abstract: The development of the Bielik v3 PL series, encompassing both the 7B and 11B parameter variants, represents a significant milestone in the field of la

Tutorials

Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards

arXiv:2510.01544v2 Announce Type: replace Abstract: Diffusion-based large language models offer a non-autoregressive alternative for text generation, but enabling them to perform complex reasoning rem

tutorialsarxiv-cs-ai

Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models

arXiv:2604.10985v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have rapidly advanced by leveraging powerful pre-trained Large Language Models (LLMs) as core reasoning backbones. As new

Do Thought Streams Matter? Evaluating Reasoning in Gemini Vision-Language Models for Video Scene Understanding

arXiv:2604.11177v1 Announce Type: new Abstract: We benchmark how internal reasoning traces, which we call thought streams, affect video scene understanding in vision-language models. Using four config

Does Your VFM Speak Plant? The Botanical Grammar of Vision Foundation Models for Object Detection

arXiv:2604.09920v1 Announce Type: new Abstract: Vision foundation models (VFMs) offer the promise of zero-shot object detection without task-specific training data, yet their performance in complex ag

applicationsarxiv-cs-cv

Local Ai

Fairboard: a quantitative framework for equity assessment of healthcare models

arXiv:2604.09656v1 Announce Type: cross Abstract: Despite there now being more than 1,000 FDA-authorised AI medical devices, formal equity assessments -- whether model performance is uniform across pa

local-aiarxiv-cs-ai

FlowHijack: A Dynamics-Aware Backdoor Attack on Flow-Matching Vision-Language-Action Models

arXiv:2604.09651v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are emerging as a cornerstone for robotics, with flow-matching policies like pi_0 showing great promise in generatin

researcharxiv-cs-cv

Generation-Augmented Generation: A Plug-and-Play Framework for Private Knowledge Injection in Large Language Models

arXiv:2601.08209v3 Announce Type: replace Abstract: In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, d

Grounded World Model for Semantically Generalizable Planning

arXiv:2604.11751v1 Announce Type: cross Abstract: In Model Predictive Control (MPC), world models predict the future outcomes of various action proposals, which are then scored to guide the selection

HiEdit: Lifelong Model Editing with Hierarchical Reinforcement Learning

arXiv:2604.11214v1 Announce Type: new Abstract: Lifelong model editing (LME) aims to sequentially rectify outdated or inaccurate knowledge in deployed LLMs while minimizing side effects on unrelated i

How Alignment Routes: Localizing, Scaling, and Controlling Policy Circuits in Language Models

arXiv:2604.04385v3 Announce Type: replace-cross Abstract: This paper localizes the policy routing mechanism in alignment-trained language models. An intermediate-layer attention gate reads detected co

HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation

arXiv:2604.09629v1 Announce Type: new Abstract: Humor generation poses a significant challenge for Large Language Models (LLMs), because their standard training objective - predicting the most likely

Immunizing 3D Gaussian Generative Models Against Unauthorized Fine-Tuning via Attribute-Space Traps

arXiv:2604.09688v1 Announce Type: new Abstract: Recent large-scale generative models enable high-quality 3D synthesis. However, the public accessibility of pre-trained weights introduces a critical vu

Minimizing classical resources in variational measurement-based quantum computation for generative modeling

arXiv:2604.11578v1 Announce Type: cross Abstract: Measurement-based quantum computation (MBQC) is a framework for quantum information processing in which a computational task is carried out through on

MoveFM-R: Advancing Mobility Foundation Models via Language-driven Semantic Reasoning

arXiv:2509.22403v2 Announce Type: replace Abstract: Mobility Foundation Models (MFMs) have advanced the modeling of human movement patterns, yet they face a ceiling due to limitations in data scale an

researcharxiv-cs-lg

Neural Generalized Mixed-Effects Models

model-releasesarxiv-cs-lg

arXiv:2604.10976v1 Announce Type: cross Abstract: Generalized linear mixed-effects models (GLMMs) are widely used to analyze grouped and hierarchical data. In a GLMM, each response is assumed to follo

Safety

Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility

arXiv:2602.03402v3 Announce Type: replace Abstract: Vision language models (VLMs) extend the reasoning capabilities of large language models (LLMs) to cross-modal settings, yet remain highly vulnerabl

safetyarxiv-cs-ai

RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation

arXiv:2604.09814v1 Announce Type: new Abstract: Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degr

SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions

arXiv:2307.01139v2 Announce Type: replace-cross Abstract: Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less

VeriInteresting: An Empirical Study of Model Prompt Interactions in Verilog Code Generation

arXiv:2603.08715v2 Announce Type: replace-cross Abstract: Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between mod

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting

arXiv:2604.10544v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have recently achieved remarkable success in universal forecasting by leveraging large-scale pretraining on dive

Why Do Large Language Models Generate Harmful Content?

arXiv:2604.11663v1 Announce Type: new Abstract: Large Language Models (LLMs) have been shown to generate harmful content. However, the underlying causes of such behavior remain under explored. We prop

researcharxiv-cs-ai

Safety

A Representation-Level Assessment of Bias Mitigation in Foundation Models