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 Machine Learning

Oct 2

Learning to Select Source-Traceable Evidence for Language-Model Prediction from Irregular Clinical Time Series

arXiv:2605.20292v2 Announce Type: replace Abstract: Numerical time-series models effectively process irregular electronic health record (EHR) trajectories, but do not expose which temporal patterns s...

By Kwanhyung Lee, Juhwan Choi, Jongheon Kim, Joohyung Lee, Hyeongwon Jang, Jeonguk Lee, Jisoo Jung, Eunho Yang

llms benchmarks

arXiv Machine Learning

Oct 2

$\textit{BlockFormer}$ : Transformer-based inference from genomic contact maps

arXiv:2605.21617v3 Announce Type: replace Abstract: Locating genomic features from genomic contact maps, such as centromere identification from genome-wide chromosome conformation capture techniques,...

By Elo\"ise Touron, Pedro L. C. Rodrigues, Julyan Arbel, Nelle Varoquaux, Michael Arbel

llms safety

arXiv Machine Learning

Oct 2

One QK Channel, Many Sources: Tracing Low-Precision Attention Collapse

arXiv:2608.02091v2 Announce Type: replace Abstract: A bfloat16 transformer can train normally, then collapse abruptly. Prior work links collapse to structured attention errors and shows QK normalizat...

By Shuxiao Xie, Shuyang Xie, Yuan Cao, Dezhi Ran, Wei Yang, Tao Xie

llms

arXiv Machine Learning

Oct 2

Steer-to-Detect: Probing Hidden Representations for Detection of LLM-Generated Texts

arXiv:2605.12890v2 Announce Type: replace-cross Abstract: The rapid advancement of large language models (LLMs) has made machine-generated text increasingly difficult to distinguish from human-writte...

By Luxu Liang, Xiang Li

llms safety

arXiv Machine Learning

Oct 2

GeoFP8: Geometry-Aware FP8 Gradient Compression for Distributed LLM Training

arXiv:2607.07494v2 Announce Type: replace-cross Abstract: Gradient communication is a primary scaling bottleneck in large language model (LLM) pretraining. Communicating gradients in low-precision fo...

By Jieying Wang, Zizhong Wang, Fangru Linghu, Shuyuan Fan, Jiajia Li, Zhao Zhang

llms efficiency

arXiv Computer Vision

Oct 2

Query Independent Variable Rate Visual Token Coding

arXiv:2610.00204v1 Announce Type: new Abstract: Visual-token compression for vision--language models is posed almost entirely as a selection problem: decide which tokens to keep and discard the rest....

By Hongbo Zhang, Zihao Yang, Liuyang Song, Daqian Yang, Haoyang Yao, Yan Wen, Zhengtao Yao

llms efficiency benchmarks

arXiv Computer Vision

Oct 2

Memorizon: Training World Models Beyond Their Context Window

arXiv:2610.00544v1 Announce Type: new Abstract: Streaming world models should render a place consistently across repeated visits. Directly supervising such revisits requires training samples that cap...

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

llms

arXiv Computer Vision

Oct 2

FORTE: Adaptive Scoring and Exact Keyframe Selection for Long-Video Question Answering

arXiv:2610.00573v1 Announce Type: new Abstract: Query-aware keyframe selection enables multimodal large language models (MLLMs) to process long videos using only a small set of question-relevant fram...

By Haifeng Huang, Biyin Xu, Chunsheng Xin, Yang Li

llms nlp multimodal benchmarks

arXiv Computer Vision

Oct 2

Paying for Too Many Tokens? Valid and Cost-Efficient Multimodal LLM Annotation with Simple Heuristics

arXiv:2610.00809v1 Announce Type: new Abstract: Vision-Language Models (VLMs) enable video annotation at scale, but costs accumulate quickly: processing a typical 60-second short-form video at one fr...

By Zhixi Zhu, Kristina Gligoric

llms multimodal

arXiv Computer Vision

Oct 2

Machine Translation for Sign Languages

arXiv:2610.00881v1 Announce Type: new Abstract: Sign language machine translation has progressed substantially over the past decade, evolving from isolated sign recognition to end-to-end translation...

By Ozge Mercanoglu Sincan, Anton Pelykh, Edward Fish, Harry Walsh, JianHe Low, Karahan Sahin, Oline Ranum, Sobhan Asasi, Steven Emery, Richard Bowden

llms computer-vision nlp

arXiv Computer Vision

Oct 2

Video-Index: A Curated Meta-Benchmark for Video Understanding

arXiv:2610.00960v1 Announce Type: new Abstract: A video benchmark should reward the capability it claims to measure, yet models can exploit answer options, question text, or partial visual evidence....

By Enxin Song, Yinuo Xu, Shusheng Yang, Wenhao Chai, Jiatao Gu

llms agents benchmarks

arXiv Computer Vision

Oct 2

VIEScore2: Unified Image Evaluation with Spatially Grounded Explanations

arXiv:2610.00994v1 Announce Type: new Abstract: Existing synthetic image evaluators typically provide only a scalar quality score and do not identify the image regions that support it. We introduce V...

By Xianda Du, Max Ku, Weiming Ren, Zhi Rui Tam, Chunlin Ren, Ping Nie, Min-Hung Chen, Wenhu Chen

llms diffusion fine-tuning multimodal benchmarks

arXiv Computer Vision

Oct 2

Towards Automatic Video Annotation with ASH: Zero-Shot Open-Vocabulary Multi-Object Tracking and Segmentation

arXiv:2610.01022v1 Announce Type: new Abstract: Memory-attention-based Video Instance Segmentation (VIS) methods have demonstrated strong zero-shot tracking capability, yet their substantial memory r...

By Arash Rocky, Q. M. Jonathan Wu

llms computer-vision benchmarks

arXiv Computer Vision

Oct 2

HAWK: Rethinking Multimodal Drafting for Speculative Decoding

arXiv:2610.00623v1 Announce Type: new Abstract: Speculative decoding has achieved substantial lossless speedups for LLMs, but remains less effective for large vision-language models (LVLMs), where li...

By Wenhan Yang, Anirudh Rao, Ashwin Chandra

llms efficiency multimodal benchmarks

arXiv Computer Vision

Oct 2

Skeleton-and-Strategy Prompting: Training-Free Negation Understanding for Vision-Language Models

arXiv:2610.01180v1 Announce Type: new Abstract: Despite the strong performance of Vision-Language Models (VLMs) on a wide range of visual question answering (VQA) tasks, these models consistently str...

By Yuliang Cai, Mohammad Rostami, Jesse Thomason

llms nlp multimodal benchmarks

arXiv Computer Vision

Oct 2

FlashBack: Knowing When to Remember in Streaming Vision-Language Models

arXiv:2610.01192v1 Announce Type: new Abstract: Streaming vision-language models must process continuously growing video streams under a bounded compute budget, creating a persistent tension between...

By Yi Chen, MingMing Yu, Rui-Qi Wang, Boran Wang, Xiaohang Cao, Chu Tang, Jingmin Chen, Jie Gu

llms multimodal

arXiv Computer Vision

Oct 2

FFBL-Coop: Association-Decoupled Cooperative 3D Multi-Object Tracking

arXiv:2610.01750v1 Announce Type: new Abstract: Cooperative 3D tracking must integrate complementary observations across agents and time while maintaining consistent identities. When evidence integra...

By Haoxin Wu, Xiaokai Bai

llms agents

arXiv Computer Vision

Oct 2

GIFTBench: Diagnosing Generalization in Image Forgery Localization and Informing Model Design

arXiv:2610.01778v1 Announce Type: new Abstract: Reliable evaluation of image forgery localization (IFL) requires assessing models under diverse distribution changes, yet existing benchmarks often cov...

By Baoke Dou, Ziye Wang, Hao Wang, Guoqing Cai, Wende Tan, Chenyang Si, Liucheng Guo, Yueming Lyu

llms robotics benchmarks

arXiv Computer Vision

Oct 2

Fewer Tokens, Better Action: GPT-6 Astra Robot Agents with 14% Higher Success Rate but 65% Fewer Tokens

arXiv:2610.01939v1 Announce Type: new Abstract: Vision language model (VLM) agents can control robots through visual feedback and action primitives, but repeated model invocations and redundant obser...

By Ruiyang Si, Jianxin Bi, Shunyu Yang, Rui Ni, Wenbo Huang, Qiang Wang, Shulong Jiang, Duomin Wang, Xiuyu Li, Haiwen Feng, Zhen Dong, Daquan Zhou

llms agents robotics multimodal

arXiv Computer Vision

Oct 2

Token-Level Video Reinforcement Learning

arXiv:2610.01973v1 Announce Type: new Abstract: Reinforcement learning (RL) for video generation usually assigns one scalar reward to an entire sampled video. Yet a video is not uniformly flawed: som...

By Yifan Wang, Gordon Guocheng Qian, Yanyu Li, Anil Kag, Yun Fu

llms diffusion reinforcement-learning multimodal

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