Large language models

Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.

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arXiv Computer Vision

Sep 22

ZIL: Zero-shot Image-to-LiDAR Registration

arXiv:2609.22716v1 Announce Type: new Abstract: Image-to-LiDAR registration estimates the camera pose of an image with respect to a LiDAR point cloud. It has diverse applications in autonomous drivin...

By Zijun Li, Xiaotian Sun, Xuelun Shen, Yao Dai, Sheng Ao, Yangyang Shi, Jakob Engel, Zhipeng Cai, Cheng Wang

llms agents robotics benchmarks

arXiv Computer Vision

Sep 22

Planning and Rendering in Concert: DeepFusion of Autoregressive Layouts and Diffusion for Visual Text Generation

arXiv:2609.22916v1 Announce Type: new Abstract: Generating text-rich images from prompts requires both textual fidelity and the coherent integration of text into the surrounding image. An explicit la...

By Guanqiao Chen, Jingru Tan, Dongxing Mao, Catherine Chen, Zijian Du, Libo Qin, Hu Jian Guo, Alex Jinpeng Wang

llms agents diffusion benchmarks

arXiv Computer Vision

Sep 22

Vision-Wireless Fusion for Multi-User Localization: A Cross-Modal Transformer Approach

arXiv:2609.23372v1 Announce Type: new Abstract: Accurate multi-user localization is challenging in complex urban environments, where wireless measurements can become ambiguous under noise, blockage,...

By Can Zheng, Jiguang He, Guofa Cai, Henk Wymeersch, Merouane Debbah

llms multimodal

arXiv Computer Vision

Sep 22

ProxyBuild: Text-Guided Structured 3D Building Generation with Mesh-Anchored Procedural Proxies

arXiv:2609.23386v1 Announce Type: new Abstract: Text-guided 3D building generation holds tremendous application potential, yet existing generative models typically output inseparable single meshes or...

By Xiang Tang, Ruotong Li, Xiaopeng Fan

llms

arXiv Computer Vision

Sep 22

Detecting Phone-Induced Pedestrian Distraction via a Multimodal Fusion Transformer

arXiv:2609.23507v1 Announce Type: new Abstract: The increasing reliance on mobile phones has made phone-induced pedestrian distraction increasingly prevalent. Activities such as texting, watching vid...

By Yuanzhe Li, Hounian Liu, Xiaotong Chang, Yidi Huang

llms agents multimodal

arXiv Computer Vision

Sep 22

Transferring Visual Explanations: How Cross-Architecture Knowledge Distillation Affects Model Interpretability

arXiv:2609.23561v1 Announce Type: new Abstract: Deploying efficient neural networks is essential in resource-constrained environments, yet compact models often sacrifice interpretability - a critical...

By Aleks Czufarow, Ihor Babin

llms agents robotics efficiency safety

arXiv Computer Vision

Sep 22

Which Terrain Is Better? Preference Learning with VLM Prototypes for Off-Road Traversability Ranking

arXiv:2609.23673v1 Announce Type: new Abstract: In vision-based off-road navigation, a robot needs to know not only which obstacles to avoid but also which terrain is better. The first is handled by...

By Ji-Hoon Hwang, Jisung Bae, E-In Son, Dong-Wook Kim, Jung-Taak Kim, Seung-Woo Seo

llms computer-vision robotics multimodal

arXiv Computer Vision

Sep 22

Layer-Aware Position Embeddings for Visual Token Pruning in Multimodal Large Language Models

arXiv:2609.23715v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) incur substantial computational overhead due to the reliance on hundreds of visual tokens to represent images....

By Yahong Wang, Zhangkai Ni, Juncheng Wu, Yuyin Zhou, Ying Wen, Lianghua He

llms rag efficiency multimodal benchmarks

arXiv Computer Vision

Sep 22

VGGT-Prime: Compute-Adaptive Mixture-of-Heads for Efficient Visual Geometry Transformers

arXiv:2609.23733v1 Announce Type: new Abstract: Feed-forward visual geometry models such as the Visual Geometry Grounded Transformer (VGGT) have recently enabled direct 3D reconstruction from multi-v...

By Abteen Arab, Guile Wu, Chengjie Huang, Dongfeng Bai

llms efficiency

arXiv Computer Vision

Sep 22

A paired synthetic construction-site image dataset for robust computer vision under adverse conditions

arXiv:2609.24075v1 Announce Type: new Abstract: Computer-vision systems used for construction monitoring can degrade under adverse environmental and visual conditions, yet such conditions remain unde...

By Viet Huy Duong, Ruoxin Xiong, Md Abdullah Al Forhad, Weishi Shi

llms rag computer-vision nlp multimodal safety

arXiv Computer Vision

Sep 22

LegendBench: A Diagnostic Benchmark for Legend Understanding with Counterfactual Interventions

arXiv:2609.24172v1 Announce Type: new Abstract: Legends are fundamental to chart understanding, as reliable interpretation requires correctly binding legend entries to corresponding visual marks. Whi...

By Xinnuo Zhang, Zhike Tang, Jing Xu, Haoyuan Zhao, Weikai Yang

llms fine-tuning multimodal benchmarks

arXiv Computer Vision

Sep 22

Document Retrieval-Aware Chunking (D-RAC): Universal Retrieval-Aware Ingestion of Enterprise Documents via PDF Normalization and Multimodal Markdown Conversion

arXiv:2609.24220v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems over enterprise knowledge bases must ingest heterogeneous document formats -- PDFs, Word documents, presen...

By Uday Allu (AI Research Team Yellow.ai), Abhivanth Sivaprakash (AI Research Team Yellow.ai), Pratik Singh (AI Research Team Yellow.ai), Aman Manocha (AI Research Team Yellow.ai)

llms rag agents computer-vision multimodal benchmarks safety

arXiv Computer Vision

Sep 22

Hierarchical Prompt Learning for Hyperbolic Vision-Language Models

arXiv:2609.24276v1 Announce Type: new Abstract: Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstr...

By Andro Erdelez, Pascal Mettes, Behzad Bozorgtabar

llms rag multimodal benchmarks

arXiv Computer Vision

Sep 22

STA-TFM: Spatio-Temporal Aggregation Across Views TransForMer for Pose Estimation

arXiv:2609.24482v1 Announce Type: new Abstract: Monocular 3D human pose estimation (HPE) remains challenging due to depth ambiguity, occlu- sions, and the need for temporal consistency. While multi-v...

By Mena Kamel, Natalie Won, Amrut Sarangi, Sven Jager, Albert Pla Planas

llms computer-vision

arXiv Computer Vision

Sep 22

Brain Metastases Segmentation for BraTS 2026 Task 1: A Multi-Architecture Comparison

arXiv:2609.24769v1 Announce Type: new Abstract: Brain metastases are the most common intracranial malignancy, occurring in roughly 30% of patients with primary solid tumors and carrying a median surv...

By Mahdi Islam, Musarrat Tabassum

llms computer-vision

arXiv Computer Vision

Sep 22

INTCORT: Training-Free Spatial Reasoning Enhancement for Vision-Language Models via Input Transformations and Confidence Routing

arXiv:2609.24813v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in multimodal tasks, yet they still exhibit poor ability in spatial reasoning....

By Haoran Sun, Jingqi Xu, Yanhui Li, Enci Liu, Kaidi Xu, Yanwei Liu

llms multimodal benchmarks

arXiv Computer Vision

Sep 22

DTKDP: A Dual Teacher Knowledge Distillation and Pruning Framework for Lightweight Oriented SAR Ship Detection

arXiv:2609.24872v1 Announce Type: new Abstract: Two-stage oriented detectors achieve high localization accuracy in synthetic aperture radar (SAR) ship detection, but their large backbones, feature py...

By Yuming Li, Fan Zhang, Alin M. Achim

llms efficiency safety

arXiv Computer Vision

Sep 22

GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers

arXiv:2506.11784v2 Announce Type: replace Abstract: Vision Transformers (ViTs) are essential in computer vision but are computationally intensive, too. Model quantization, particularly to low bit-wid...

By Guang Liang, Xinyao Liu, Jianxin Wu

llms computer-vision efficiency

arXiv Computer Vision

Sep 22

VRWKV-Editor: Reducing quadratic complexity in transformer-based video editing

arXiv:2509.25998v4 Announce Type: replace Abstract: In light of recent progress in video editing, deep learning models focusing on both spatial and temporal dependencies have emerged as the primary m...

By Abdelilah Aitrouga, Youssef Hmamouche, Amal El Fallah Seghrouchni

llms diffusion benchmarks safety

arXiv Computer Vision

Sep 22

BackdoorVLM: A Benchmark for Backdoor Attacks and Defenses on Vision-Language Models

arXiv:2511.18921v2 Announce Type: replace Abstract: Backdoor attacks undermine the reliability and trustworthiness of machine learning systems by injecting hidden behaviors that can be maliciously ac...

By Juncheng Li, Yige Li, Hanxun Huang, Yunhao Chen, Xin Wang, Yixu Wang, Xingjun Ma, Yu-Gang Jiang

llms nlp multimodal benchmarks safety

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