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MultiWikiQA: A Reading Comprehension Benchmark in 300 Languages
Dan Saattrup Smart
https://arxiv.org/abs/2509.04111 https://arxiv.org/pdf/2509.04111

MultiWikiQA: A Reading Comprehension Benchmark in 300+ Languages
We introduce a new reading comprehension dataset, dubbed MultiWikiQA, which covers 306 languages. The context data comes from Wikipedia articles, with questions generated by an LLM and the answers appearing verbatim in the Wikipedia articles. We conduct a crowdsourced human evaluation of the fluency of the generated questions across 30 of the languages, providing evidence that the questions are of good quality. We evaluate 6 different language models, both decoder and encoder models of varying …

A Framework Leveraging Large Language Models for Autonomous UAV Control in Flying Networks
Diana Nunes, Ricardo Amorim, Pedro Ribeiro, Andr\'e Coelho, Rui Campos
https://arxiv.org/abs/2506.04404

A Framework Leveraging Large Language Models for Autonomous UAV Control in Flying Networks
This paper proposes FLUC, a modular framework that integrates open-source Large Language Models (LLMs) with Unmanned Aerial Vehicle (UAV) autopilot systems to enable autonomous control in Flying Networks (FNs). FLUC translates high-level natural language commands into executable UAV mission code, bridging the gap between operator intent and UAV behaviour. FLUC is evaluated using three open-source LLMs - Qwen 2.5, Gemma 2, and LLaMA 3.2 - across scenarios involving code generation and mission …

D.C. judge excoriates Trump policing surge, demands answers from Pirro
A federal magistrate judge overseeing a torrent of cases during President Donald Trump’s policing surge in D.C.
condemned administration officials at a hearing Thursday,
saying they were trampling people’s rights
by overcharging them with felonies and then moving slowly to dismiss the weakest cases
while the defendants languished in jail.

The blistering remarks by Magistrate Judge Zia …

D.C. judge excoriates Trump policing surge, demands answers from Pirro
Responding to Magistrate Judge Zia M. Faruqui’s remarks regarding President Donald Trump’s policing surge in D.C., U.S. Attorney Jeanine Pirro said the judge “has allowed his politics to consistently cloud his judgment.”

TikTok launches its e-commerce platform, TikTok Shop, in Japan, marking its 17th market, following launches in the US, the UK, Malaysia, Thailand, and others (Danielle Popov/South China Morning Post)
https://www.scmp.com/tech/big-tech/article

TikTok Shop launches in Japan as app faces uncertainty in US
The popular short-video app is seeking to diversify its global footprint while reducing its reliance on the US market.

CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection
Qiyu Chen, Zhen Qu, Wei Luo, Haiming Yao, Yunkang Cao, Yuxin Jiang, Yinan Duan, Huiyuan Luo, Chengkan Lv, Zhengtao Zhang
https://arxiv.org/abs/2508.03447

CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection
Recently, large pre-trained vision-language models have shown remarkable performance in zero-shot anomaly detection (ZSAD). With fine-tuning on a single auxiliary dataset, the model enables cross-category anomaly detection on diverse datasets covering industrial defects and medical lesions. Compared to manually designed prompts, prompt learning eliminates the need for expert knowledge and trial-and-error. However, it still faces the following challenges: (i) static learnable tokens struggle to …

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Yifan Zhong, Fengshuo Bai, Shaofei Cai, Xuchuan Huang, Zhang Chen, Xiaowei Zhang, Yuanfei Wang, Shaoyang Guo, Tianrui Guan, Ka Nam Lui, Zhiquan Qi, Yitao Liang, Yuanpei Chen, Yaodong Yang
https://arxiv.org/abs/2507.01925

A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
The remarkable advancements of vision and language foundation models in multimodal understanding, reasoning, and generation has sparked growing efforts to extend such intelligence to the physical world, fueling the flourishing of vision-language-action (VLA) models. Despite seemingly diverse approaches, we observe that current VLA models can be unified under a single framework: vision and language inputs are processed by a series of VLA modules, producing a chain of \textit{action tokens} that …

Evaluating the Efficacy of Large Language Models for Generating Fine-Grained Visual Privacy Policies in Homes
Shuning Zhang, Ying Ma, Xin Yi, Hewu Li
https://arxiv.org/abs/2508.00321

Evaluating the Efficacy of Large Language Models for Generating Fine-Grained Visual Privacy Policies in Homes
The proliferation of visual sensors in smart home environments, particularly through wearable devices like smart glasses, introduces profound privacy challenges. Existing privacy controls are often static and coarse-grained, failing to accommodate the dynamic and socially nuanced nature of home environments. This paper investigates the viability of using Large Language Models (LLMs) as the core of a dynamic and adaptive privacy policy engine. We propose a conceptual framework where visual data …

A Privacy-Preserving Recommender for Filling Web Forms Using a Local Large Language Model
Amirreza Nayyeri, Abbas Rasoolzadegan
https://arxiv.org/abs/2509.01527 https://

A Privacy-Preserving Recommender for Filling Web Forms Using a Local Large Language Model
Web applications are increasingly used in critical domains such as education, finance, and e-commerce. This highlights the need to ensure their failure-free performance. One effective method for evaluating failure-free performance is web form testing, where defining effective test scenarios is key to a complete and accurate evaluation. A core aspect of this process involves filling form fields with suitable values to create effective test cases. However, manually generating these values is time…

RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models
Zhaoyan Gong, Juan Li, Zhiqiang Liu, Lei Liang, Huajun Chen, Wen Zhang
https://arxiv.org/abs/2509.03995

RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models
Current temporal knowledge graph question answering (TKGQA) methods primarily focus on implicit temporal constraints, lacking the capability of handling more complex temporal queries, and struggle with limited reasoning abilities and error propagation in decomposition frameworks. We propose RTQA, a novel framework to address these challenges by enhancing reasoning over TKGs without requiring training. Following recursive thinking, RTQA recursively decomposes questions into sub-problems, solves …

Are We on the Right Way for Assessing Document Retrieval-Augmented Generation?
Wenxuan Shen, Mingjia Wang, Yaochen Wang, Dongping Chen, Junjie Yang, Yao Wan, Weiwei Lin
https://arxiv.org/abs/2508.03644

Are We on the Right Way for Assessing Document Retrieval-Augmented Generation?
Retrieval-Augmented Generation (RAG) systems using Multimodal Large Language Models (MLLMs) show great promise for complex document understanding, yet their development is critically hampered by inadequate evaluation. Current benchmarks often focus on specific part of document RAG system and use synthetic data with incomplete ground truth and evidence labels, therefore failing to reflect real-world bottlenecks and challenges. To overcome these limitations, we introduce Double-Bench: a new large…