Tootfinder

GAMA: A General Anonymizing Multi-Agent System for Privacy Preservation Enhanced by Domain Rules and Disproof Method
Hailong Yang, Renhuo Zhao, Guanjin Wang, Zhaohong Deng
https://arxiv.org/abs/2509.10018

GAMA: A General Anonymizing Multi-Agent System for Privacy Preservation Enhanced by Domain Rules and Disproof Method
With the rapid advancement of Large Language Model (LLM), LLM-based agents exhibit exceptional abilities in understanding and generating natural language, facilitating human-like collaboration and information transmission in LLM-based Multi-Agent System (MAS). High-performance LLMs are often hosted on remote servers in public spaces. When tasks involve privacy data, MAS cannot securely utilize these LLMs without implementing privacy-preserving mechanisms. To address this challenge, we propose a…

Anonymous Coach Pinpoints Biggest Flaw in Geno Smith’s Game https://heavy.com/sports/nfl/las-vegas-raiders/geno-smith-the-athletic-qb-tiers/?adt_ei=[email]

Grüße gehen raus an @…

🕹️ Interview: The First Descendant Director on the Issues with the Game And How They're Fixing Them
https://www.animenewsnetwork.com/interview/2025-09-27/the-first-descendant-director-on-th…

Interview: The First Descendant Director on the Issues with the Game And How They're Fixing Them
We sat down with Director Min Seok Joo at Tokyo Game Show 2025 to talk frankly about the issues currently facing the game and their plans to overcome them.

Anonymous monitoring enables turn-taking and sustainablity in collective resource governance: Multi-player evolutionary dynamical-systems game
Kenji Itao, Kunihiko Kaneko
https://arxiv.org/abs/2507.22555

Anonymous monitoring enables turn-taking and sustainablity in collective resource governance: Multi-player evolutionary dynamical-systems game
Sustainable resource use in large societies requires social institutions that specify acceptable behavior and punish violators. Because mutual monitoring becomes prohibitively costly as populations grow, we examine whether sustainability can be maintained when only anonymized information is available. Using the evolutionary dynamical-systems game framework, we model the common-pool resource management game. In the model, each player's harvesting decisions shape the resource dynamics and depend …

DarkStream: real-time speech anonymization with low latency
Waris Quamer, Ricardo Gutierrez-Osuna
https://arxiv.org/abs/2509.04667 https://arxiv.org/pdf/25…

DarkStream: real-time speech anonymization with low latency
We propose DarkStream, a streaming speech synthesis model for real-time speaker anonymization. To improve content encoding under strict latency constraints, DarkStream combines a causal waveform encoder, a short lookahead buffer, and transformer-based contextual layers. To further reduce inference time, the model generates waveforms directly via a neural vocoder, thus removing intermediate mel-spectrogram conversions. Finally, DarkStream anonymizes speaker identity by injecting a GAN-generated …

AV-EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Omni-modal LLMS with Audio-visual Cues
Krish Patel, Dingkun Zhou, Ajay Kankipati, Akshaj Gupta, Zeyi Austin Li, Mohul Shukla, Vibhor Narang, Sara Kofman, Zongli Ye, Grace Wang, Xiaoyu Shi, Tingle Li, Guan-Ting Lin, Kan Jen Cheng, Huang-Cheng Chou, Jiachen Lian, Gopala Anumanchipalli
https://

AV-EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Omni-modal LLMS with Audio-visual Cues
Emotions conveyed through voice and face shape engagement and context in human-AI interaction. Despite rapid progress in omni-modal large language models (LLMs), the holistic evaluation of emotional reasoning with audiovisual cues remains limited. To address this gap, we introduce AV-EMO-Reasoning, a benchmark designed to systematically assess emotional coherence in LLMs. The framework leverages a curated, single- and multi-turn synthetic audiovisual corpus with a real-world set and is assessed…

TravelBench : Exploring LLM Performance in Low-Resource Domains
Srinivas Billa, Xiaonan Jing
https://arxiv.org/abs/2510.02719 https://arxiv.org/pdf/2510.02…

TravelBench : Exploring LLM Performance in Low-Resource Domains
Results on existing LLM benchmarks capture little information over the model capabilities in low-resource tasks, making it difficult to develop effective solutions in these domains. To address these challenges, we curated 14 travel-domain datasets spanning 7 common NLP tasks using anonymised data from real-world scenarios, and analysed the performance across LLMs. We report on the accuracy, scaling behaviour, and reasoning capabilities of LLMs in a variety of tasks. Our results confirm that gen…

Jeszcze jedno zdjęcie archiwalne. Tym razem przed pożarami ostrzega #Choszczno, na Pomorzu Zachodnim. Rok 2018.
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