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 AI

Oct 1

MoEless: Efficient MoE LLM Serving with Serverless Experts

arXiv:2603.06350v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly adopt Mixture-of-Experts (MoE) architectures to scale efficiently under stringent resource constrai...

By Hanfei Yu, Bei Ouyang, Shwai He, Ang Li, Hao Wang

llms efficiency benchmarks

arXiv AI

Oct 1

VisionFoundry: Teaching VLMs Visual Perception with Synthetic Images

arXiv:2604.09531v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) still struggle with visual perception tasks such as spatial understanding and viewpoint recognition, largely be...

By Guanyu Zhou, Yida Yin, Wenhao Chai, Shengbang Tong, Xingyu Fu, Zhuang Liu

llms diffusion reinforcement-learning fine-tuning multimodal benchmarks

arXiv Computation and Language

Oct 1

Conformal Factuality Control for Multi-Hop Retrieval-Augmented Generation

arXiv:2609.38222v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can ground large language models in external evidence, but retrieved context does not guarantee that generated cla...

By Muhammad Aimal Rehman, Chi-Kuang Yeh

llms rag

arXiv Computation and Language

Oct 1

How Much Is an AI Token Worth? Scaling Laws for Wild AI-Generated Web Text

arXiv:2609.40295v1 Announce Type: new Abstract: Web text makes up the majority of pretraining data and is increasingly AI-generated. After applying FineWeb quality filtering, we find that 27.5% of to...

By Jenna Russell, Ben Glickenhaus, Katherine Thai, John Wieting, Mohit Iyyer, Max Spero, Bradley Emi

llms

arXiv Computation and Language

Oct 1

JuryFlow: Disagreement-Guided Human-in-the-Loop Multi-Agent Evaluation

arXiv:2609.40103v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as automated judges for AI-generated content, yet a single judge is unreliable and even a panel...

By Mufeng Yang, Junwei Yu, Yepeng Ding

llms agents benchmarks

arXiv Computation and Language

Oct 1

When Does a Spoken Agent Have Enough Evidence to Act? The PACT-SLM Contract Test

arXiv:2609.38232v1 Announce Type: cross Abstract: Streaming spoken agents may take an external action before the available speech supports it, yet final-turn scores do not reveal whether each observe...

By Mengzhe Geng

llms agents

arXiv Computer Vision

Oct 1

Strike a Chord! Modal Kinetic Typography

arXiv:2609.38325v1 Announce Type: new Abstract: We introduce modal kinetic typography, which animates a vector glyph to express a semantic concept while keeping it legible. Our key idea is to build m...

By Maham Tanveer, Jiyeon Han, Nanxuan Zhao, Hao Zhang

llms diffusion efficiency safety

arXiv Computer Vision

Oct 1

VidHarness: Evolving Agent Harnesses for Cost-Efficient Long Video Understanding

arXiv:2609.38413v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer questions about hour-long videos, but processing every frame is prohibitively expensive, even though the evide...

By Susan Liang, Jianmin Wu, Daxiang Dong

llms agents multimodal benchmarks

arXiv Computer Vision

Oct 1

ThinkV2V: Unleashing the Reasoning Capability of MLLMs for Instruction-Guided Video Editing

arXiv:2609.38541v1 Announce Type: new Abstract: Instruction-guided video editing has made significant progress, yet existing methods use multimodal large language models (MLLMs) primarily as semantic...

By Donghao Zhou, Haoyang He, Fan Zhang, Hao Yang, Guisheng Liu, Xin Gao, Zhongwei Wan, Xingyuan Bu, Jie Wang, Qiangpeng Yang, Shilei Wen, Chi-Wing Fu, Pheng-Ann Heng

llms multimodal benchmarks

arXiv Computer Vision

Oct 1

Distill the Visual Evidence, Not Just the Answer: Cross-World On-Policy Distillation for Vision-Language Models

arXiv:2609.38777v1 Announce Type: new Abstract: A central goal of vision-language model (VLM) distillation is to transfer both the teacher's language capabilities and its visual understanding. Howeve...

By Yuanhao Sun, Huawei Ji, Jiaxin Ding, Luoyi Fu, Xinbing Wang

llms efficiency multimodal

arXiv Computer Vision

Oct 1

Mitigating Object Hallucination in Large Vision-Language Models via False Discovery Controlled Visual Data Splitting

arXiv:2609.38979v1 Announce Type: new Abstract: Multiple object hallucination, where large vision-language models (LVLMs) generate objects not supported by the visual input, is a persistent challenge...

By Chang Liu, Yu Tian, Rui Xie

llms multimodal benchmarks safety

arXiv Computer Vision

Oct 1

Fiber-Resolved Microstructure Quantification from Multi-Shell Diffusion MRI using Detection Transformers

arXiv:2609.39184v1 Announce Type: new Abstract: Fiber orientation and compartmental microstructure are central to the characterization of white matter tissue in diffusion MRI, yet existing methods ei...

By Sebastian Endt, Marcus Wirth, Johannes Reinhold Schlund, Marion Irene Menzel

llms diffusion computer-vision benchmarks

arXiv Computer Vision

Oct 1

Front-to-Back: Benchmarking Vision-Language Models for Asymmetric Cross-View Vehicle Re-Identification

arXiv:2609.39492v1 Announce Type: new Abstract: Matching the same vehicle across front and rear cameras is difficult because the cameras do not share a view and the vehicle's appearance changes subst...

By Moseli Mots'oehli, Thulani Babeli

llms multimodal benchmarks

arXiv Computer Vision

Oct 1

TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning

arXiv:2609.39335v1 Announce Type: new Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing met...

By Zijing Qin, Jun Zhou, Ruicheng Zhang, Jiaqi Hou, Zunnan Xu, Ronghui Li, Zhenyu Xie, Xiu Li

llms diffusion multimodal benchmarks

arXiv Computer Vision

Oct 1

MC-PanDA++: Simpler, Stronger, and More Robust Domain-Adaptive Panoptic Segmentation

arXiv:2609.39681v1 Announce Type: new Abstract: Unsupervised domain adaptation (UDA) reduces the annotation burden in panoptic segmentation by leveraging a cost-effectively labeled source domain (e.g...

By Ivan Martinovi\'c, Josip \v{S}ari\'c, Yuki M. Asano, Sini\v{s}a \v{S}egvi\'c

llms computer-vision fine-tuning benchmarks safety

arXiv Computer Vision

Oct 1

Learning Where to Look: Anatomical Grounding and Guided Attention for Cardiac MRI Vision-Language Models

arXiv:2609.39899v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) enables assessment of cardiac anatomy, ventricular function, and myocardial tissue characteristics. Clinicians...

By Bangwei Guo, Xiao Chen, Boris Mailhe, Jia Yao, Yiqing Wang, Ankush Mukherjee, Yikang Liu, Zheyuan Zhang, Hang Yu, Terrence Chen, Shanhui Sun

llms nlp multimodal

arXiv Computer Vision

Oct 1

LOCI: Spatial Linear Memory for Streaming World Models

arXiv:2609.40222v1 Announce Type: new Abstract: When a camera revisits a previously observed region, a video world model should reproduce what was there before. This requires both remembering past ob...

By Ji Xia, Tingting Liao, Xuezhi Liang, Hao Li, Guangyi Liu

llms benchmarks

arXiv Computer Vision

Oct 1

Revisiting On-policy Adversarial Black-Box Distillation: Calibrating Groupwise Reward Geometry for Effective Advantage Construction

arXiv:2609.39757v1 Announce Type: cross Abstract: Black-box distillation is a practical route for transferring capabilities from API-accessible large language models that expose only text outputs int...

By Xiao Cui, Mo Zhu, Yulei Qin, Yuze Wu, Wengang Zhou, Houqiang Li

llms efficiency safety

arXiv Computer Vision

Oct 1

SPROUT: A Scalable Diffusion Foundation Model for Multi-Crop Plant Phenotyping

arXiv:2603.27519v4 Announce Type: replace Abstract: Image-based plant phenotyping depends on dense structural understanding of crops, yet pixel-level annotation remains expensive across species, orga...

By Shuai Xiang, James Burridge, Shouyang Liu, Hao Lu, Tokihiro Fukatsu, Yinqiang Zheng, Wei Guo

llms diffusion computer-vision

arXiv Computer Vision

Oct 1

PrePARE: Pre-AA Token Pruning for Frozen Multi-View Geometry Transformers

arXiv:2605.08371v2 Announce Type: replace Abstract: Multi-view geometry transformers are feed-forward 3D foundation models that jointly predict depth maps, point maps, and camera poses for N images i...

By Haotang Li, Zhenyu Qi, Shaohan Henry Wang, Kebin Peng, Zi Wang, Qing Guo, Sen He, Huanrui Yang

llms efficiency

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