Tootfinder

Ask-to-Clarify: Resolving Instruction Ambiguity through Multi-turn Dialogue
Xingyao Lin, Xinghao Zhu, Tianyi Lu, Sicheng Xie, Hui Zhang, Xipeng Qiu, Zuxuan Wu, Yu-Gang Jiang
https://arxiv.org/abs/2509.15061

Ask-to-Clarify: Resolving Instruction Ambiguity through Multi-turn Dialogue
The ultimate goal of embodied agents is to create collaborators that can interact with humans, not mere executors that passively follow instructions. This requires agents to communicate, coordinate, and adapt their actions based on human feedback. Recently, advances in VLAs have offered a path toward this goal. However, most current VLA-based embodied agents operate in a one-way mode: they receive an instruction and execute it without feedback. This approach fails in real-world scenarios where …

Coming soon (likely this afternoon, I’m writing tests and docs and updating examples as we speak)…
This is the sort of thing you’ll be able to do with Markdown pages. Just pop any arbitrary JavaScript you want in the new script block in the front matter and then import and use components as well as plain old JavaScript tagged template variable interpolation (not shown in this example) inside your Markdown.
The screen has all the code (sans the end of the last line of CSS and the…

LLMind 2.0: Distributed IoT Automation with Natural Language M2M Communication and Lightweight LLM Agents
Yuyang Du, Qun Yang, Liujianfu Wang, Jingqi Lin, Hongwei Cui, Soung Chang Liew
https://arxiv.org/abs/2508.13920

LLMind 2.0: Distributed IoT Automation with Natural Language M2M Communication and Lightweight LLM Agents
Recent advances in large language models (LLMs) have sparked interest in their application to IoT and automation systems, particularly for facilitating device management through natural language instructions. However, existing centralized approaches face significant scalability challenges when managing and coordinating the collaboration between IoT devices of diverse capabilities in large-scale heterogeneous IoT systems. This paper introduces LLMind 2.0, a distributed IoT automation framework t…

Affordance-Based Disambiguation of Surgical Instructions for Collaborative Robot-Assisted Surgery
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
https://arxiv.org/abs/2509.14967 h…

Affordance-Based Disambiguation of Surgical Instructions for Collaborative Robot-Assisted Surgery
Effective human-robot collaboration in surgery is affected by the inherent ambiguity of verbal communication. This paper presents a framework for a robotic surgical assistant that interprets and disambiguates verbal instructions from a surgeon by grounding them in the visual context of the operating field. The system employs a two-level affordance-based reasoning process that first analyzes the surgical scene using a multimodal vision-language model and then reasons about the instruction using …

koboshi: A Base That Animates Everyday Objects
Yuta Sugiura
https://arxiv.org/abs/2508.13509 https://arxiv.org/pdf/2508.13509

koboshi: A Base That Animates Everyday Objects
We propose a base-shaped robot named "koboshi" that moves everyday objects. This koboshi has a spherical surface in contact with the floor, and by moving a weight inside using built-in motors, it can rock up and down, and side to side. By placing everyday items on this koboshi, users can impart new movement to otherwise static objects. The koboshi is equipped with sensors to measure its posture, enabling interaction with users. Additionally, it has communication capabilities, allowing multiple …

Conducting Mission-Critical Voice Experiments with Automated Speech Recognition and Crowdsourcing
Jan Janak, Kahlil Dozier, Lauren Berny, Liang Hu, Dan Rubenstein, Charles Jennings, Henning Schulzrinne
https://arxiv.org/abs/2509.13724

Conducting Mission-Critical Voice Experiments with Automated Speech Recognition and Crowdsourcing
Mission-critical voice (MCV) communications systems have been a critical tool for the public safety community for over eight decades. Public safety users expect MCV systems to operate reliably and consistently, particularly in challenging conditions. Because of these expectations, the Public Safety Communications Research (PSCR) Division of the National Institute of Standards and Technology (NIST) has been interested in correlating impairments in MCV communication systems and public safety user…

xRWA: A Cross-Chain Framework for Interoperability of Real-World Assets
Yihao Guo, Haoming Zhu, Minghui Xu, Xiuzhen Cheng, Bin Xiao
https://arxiv.org/abs/2509.12957 https://

xRWA: A Cross-Chain Framework for Interoperability of Real-World Assets
Real-World Assets (RWAs) have recently attracted increasing attention as a means of bridging traditional financial instruments with decentralized infrastructures. By representing assets such as bonds, commodities, and real estate on blockchains, RWAs can enhance liquidity, broaden accessibility, and extend the scope of decentralized finance. Industry forecasts further suggest rapid growth of tokenized RWAs in the coming years, underscoring their potential role in the evolution of digital financ…

Multi-Satellite Cooperative MIMO Transmission: Statistical CSI-Aware RSMA Precoding Design
Sangwon Jo, Seok-Hwan Park
https://arxiv.org/abs/2508.11132 https://

Multi-Satellite Cooperative MIMO Transmission: Statistical CSI-Aware RSMA Precoding Design
We investigate inter-satellite cooperative transmission in a multiple low-Earth orbit (LEO) satellite communication system to enhance spectral efficiency. Specifically, we design multiple-input multipleoutput (MIMO) precoding at LEO satellites for cooperative rate-splitting multiple access (RSMA). Given the difficulty of acquiring instantaneous channel state information (iCSI) due to long delays and Doppler effects, we formulate an ergodic max-min fairness rate (MMFR) maximization problem based…

Kling-Avatar: Grounding Multimodal Instructions for Cascaded Long-Duration Avatar Animation Synthesis
Yikang Ding, Jiwen Liu, Wenyuan Zhang, Zekun Wang, Wentao Hu, Liyuan Cui, Mingming Lao, Yingchao Shao, Hui Liu, Xiaohan Li, Ming Chen, Xiaoqiang Liu, Yu-Shen Liu, Pengfei Wan
https://arxiv.org/abs/2509.09595

Kling-Avatar: Grounding Multimodal Instructions for Cascaded Long-Duration Avatar Animation Synthesis
Recent advances in audio-driven avatar video generation have significantly enhanced audio-visual realism. However, existing methods treat instruction conditioning merely as low-level tracking driven by acoustic or visual cues, without modeling the communicative purpose conveyed by the instructions. This limitation compromises their narrative coherence and character expressiveness. To bridge this gap, we introduce Kling-Avatar, a novel cascaded framework that unifies multimodal instruction under…

Towards Native AI in 6G Standardization: The Roadmap of Semantic Communication
Ping Zhang, Xiaodong Xu, Mengying Sun, Haixiao Gao, Nan Ma, Xiaoyun Wang, Ruichen Zhang, Jiacheng Wang, Dusit Niyato
https://arxiv.org/abs/2509.12758

Towards Native AI in 6G Standardization: The Roadmap of Semantic Communication
Semantic communication (SemCom) has emerged as a transformative paradigm for future 6G networks, offering task-oriented and meaning-aware transmission that fundamentally redefines traditional bit-centric design. Recognized by leading standardization bodies including the institute of electrical and electronics engineers (IEEE) and the international telecommunication union (ITU), and actively discussed within the 3rd generation partnership project (3GPP) working groups, SemCom is rapidly gaining …