Tootfinder

Had to time-shift #LFC because of a meeting. 😠 But now I've gone FT and, wow! There is so much to unpack.
Firstly, I agree with Slot's comments. It was certainly very intense, but quality football was not possible. Newcastle seemingly poured all their frustrations about the Isak situation and wanting to be a top club into this, making it an absolute powder keg. As if winning would somehow…

Multipartite Markov Gaps and Entanglement Wedge Multiway Cuts
Norihiro Iizuka, Akihiro Miyata, Mitsuhiro Nishida
https://arxiv.org/abs/2507.15262 https://

Multipartite Markov Gaps and Entanglement Wedge Multiway Cuts
The Markov gap, defined as the difference between reflected entropy and mutual information, serves as a diagnostic for quantum recoverability and multipartite entanglement. In holographic settings, it admits a geometric interpretation as the deviation between entanglement wedge cross-sections and RT surfaces. Motivated by this holographic perspective, we propose a generalization of the Markov gap to multipartite systems by using a reflected multi-entropy. The resulting Multipartite Markov gap c…

Public Evaluation on Potential Social Impacts of Fully Autonomous Cybernetic Avatars for Physical Support in Daily-Life Environments: Large-Scale Demonstration and Survey at Avatar Land
Lotfi El Hafi, Kazuma Onishi, Shoichi Hasegawa, Akira Oyama, Tomochika Ishikawa, Masashi Osada, Carl Tornberg, Ryoma Kado, Kento Murata, Saki Hashimoto, Sebastian Carrera Villalobos, Akira Taniguchi, Gustavo Alfonso Garcia Ricardez, Yoshinobu Hagiwara, Tatsuya Aoki, Kensuke Iwata, Takato Horii, Yukiko H…

Public Evaluation on Potential Social Impacts of Fully Autonomous Cybernetic Avatars for Physical Support in Daily-Life Environments: Large-Scale Demonstration and Survey at Avatar Land
Cybernetic avatars (CAs) are key components of an avatar-symbiotic society, enabling individuals to overcome physical limitations through virtual agents and robotic assistants. While semi-autonomous CAs intermittently require human teleoperation and supervision, the deployment of fully autonomous CAs remains a challenge. This study evaluates public perception and potential social impacts of fully autonomous CAs for physical support in daily life. To this end, we conducted a large-scale demonstr…

PARCO: Phoneme-Augmented Robust Contextual ASR via Contrastive Entity Disambiguation
Jiajun He, Naoki Sawada, Koichi Miyazaki, Tomoki Toda
https://arxiv.org/abs/2509.04357 https…

PARCO: Phoneme-Augmented Robust Contextual ASR via Contrastive Entity Disambiguation
Automatic speech recognition (ASR) systems struggle with domain-specific named entities, especially homophones. Contextual ASR improves recognition but often fails to capture fine-grained phoneme variations due to limited entity diversity. Moreover, prior methods treat entities as independent tokens, leading to incomplete multi-token biasing. To address these issues, we propose Phoneme-Augmented Robust Contextual ASR via COntrastive entity disambiguation (PARCO), which integrates phoneme-aware …

Toward Ownership Understanding of Objects: Active Question Generation with Large Language Model and Probabilistic Generative Model
Saki Hashimoto, Shoichi Hasegawa, Tomochika Ishikawa, Akira Taniguchi, Yoshinobu Hagiwara, Lotfi El Hafi, Tadahiro Taniguchi
https://arxiv.org/abs/2509.12754

Toward Ownership Understanding of Objects: Active Question Generation with Large Language Model and Probabilistic Generative Model
Robots operating in domestic and office environments must understand object ownership to correctly execute instructions such as ``Bring me my cup.'' However, ownership cannot be reliably inferred from visual features alone. To address this gap, we propose Active Ownership Learning (ActOwL), a framework that enables robots to actively generate and ask ownership-related questions to users. ActOwL employs a probabilistic generative model to select questions that maximize information gain, thereby …

From Feedback to Failure: Automated Android Performance Issue Reproduction
Zhengquan Li, Zhenhao Li, Zishuo Ding
https://arxiv.org/abs/2508.11147 https://a…

From Feedback to Failure: Automated Android Performance Issue Reproduction
Mobile application performance is a vital factor for user experience. Yet, performance issues are notoriously difficult to detect within development environments, where their manifestations are often less conspicuous and diagnosis proves more challenging. To address this limitation, we propose RevPerf, an advanced performance issue reproduction tool that leverages app reviews from Google Play to acquire pertinent information. RevPerf employs relevant reviews and prompt engineering to enrich the…

GOP Senators agree to change a provision in the tax bill from a 10-year ban on state AI regulation to a 5-year ban with carve outs for issues such as copyrights (Bloomberg)
https://www.bloomberg.com/news/articles/20…

Augmented Question-guided Retrieval (AQgR) of Indian Case Law with LLM, RAG, and Structured Summaries
Vishnuprabha V, Daleesha M Viswanathan, Rajesh R, Aneesh V Pillai
https://arxiv.org/abs/2508.04710 …

Augmented Question-guided Retrieval (AQgR) of Indian Case Law with LLM, RAG, and Structured Summaries
Identifying relevant legal precedents remains challenging, as most retrieval methods emphasize factual similarity over legal issues, and current systems often lack explanations clarifying case relevance. This paper proposes the use of Large Language Models (LLMs) to address this gap by facilitating the retrieval of relevant cases, generating explanations to elucidate relevance, and identifying core legal issues all autonomously, without requiring legal expertise. Our approach combines Retrieval…

I can't believe i removed my (#)AntitrustJoke
Went something like:
Google: Why is nobody putting pressure on us to allow alternative stores and haha like we would actually cave hehehe, no way...
EU: We agree, nobody should put pressure on you on any antitrust issues.
Google: What!? You defending us as well? Thanks! Then everybody will get shitty apps forever! Great idea! We love it!
EU: Glad to help. Anyway you got F-Droid hahahaha
Google: HAHAHAHA! We…

Multi-Robot Task Planning for Multi-Object Retrieval Tasks with Distributed On-Site Knowledge via Large Language Models
Kento Murata, Shoichi Hasegawa, Tomochika Ishikawa, Yoshinobu Hagiwara, Akira Taniguchi, Lotfi El Hafi, Tadahiro Taniguchi
https://arxiv.org/abs/2509.12838

Multi-Robot Task Planning for Multi-Object Retrieval Tasks with Distributed On-Site Knowledge via Large Language Models
It is crucial to efficiently execute instructions such as "Find an apple and a banana" or "Get ready for a field trip," which require searching for multiple objects or understanding context-dependent commands. This study addresses the challenging problem of determining which robot should be assigned to which part of a task when each robot possesses different situational on-site knowledge-specifically, spatial concepts learned from the area designated to it by the user. We propose a task plannin…