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Training a spoken language understanding system, as the one in Alexa, typically requires a large human-annotated corpus of data. Manual annotations are expensive and time consuming. In Alexa Skill Kit (ASK) user experience with the skill…

计算与语言 · 计算机科学 2020-06-30 Alex Sokolov , Denis Filimonov

Effective human-robot collaboration depends on task-oriented handovers, where robots present objects in ways that support the partners intended use. However, many existing approaches neglect the humans post-handover action, relying on…

机器人学 · 计算机科学 2025-09-30 Andreea Tulbure , Rene Zurbruegg , Timm Grigat , Marco Hutter

The right response to someone who says "get ready for a party" is deeply influenced by meaning and context. For a smart home assistant (e.g., Google Home), the ideal response might be to survey the available devices in the home and change…

人机交互 · 计算机科学 2023-03-27 Evan King , Haoxiang Yu , Sangsu Lee , Christine Julien

Large Language Models (LLMs) have been widely utilized to perform complex robotic tasks. However, handling external disturbances during tasks is still an open challenge. This paper proposes a novel method to achieve robotic adaptive tasks…

机器人学 · 计算机科学 2024-08-20 Haotian Zhou , Yunhan Lin , Longwu Yan , Jihong Zhu , Huasong Min

Recent research in embodied AI has been boosted by the use of simulation environments to develop and train robot learning approaches. However, the use of simulation has skewed the attention to tasks that only require what robotics…

The language-guided robot grasping task requires a robot agent to integrate multimodal information from both visual and linguistic inputs to predict actions for target-driven grasping. While recent approaches utilizing Multimodal Large…

机器人学 · 计算机科学 2025-02-10 Houjian Yu , Mingen Li , Alireza Rezazadeh , Yang Yang , Changhyun Choi

We present our SocialBot -- Alquist~5.0 -- developed for the Alexa Prize SocialBot Grand Challenge~5. Building upon previous versions of our system, we introduce the NRG Barista and outline several innovative approaches for integrating…

机器学习 · 计算机科学 2024-02-26 Ondřej Kobza , Jan Čuhel , Tommaso Gargiani , David Herel , Petr Marek

Open world language conditioned task planning is crucial for robots operating in large-scale household environments. While many recent works attempt to address this problem using Large Language Models (LLMs) via prompting or training, a key…

机器人学 · 计算机科学 2026-02-13 Zhihong Liu , Yang Li , Rengming Huang , Cewu Lu , Panpan Cai

Reinforcement learning (RL) has recently shown impressive performance in complex game AI and robotics tasks. To a large extent, this is thanks to the availability of simulated environments such as OpenAI Gym, Atari Learning Environment, or…

计算与语言 · 计算机科学 2020-11-18 Rajkumar Ramamurthy , Rafet Sifa , Christian Bauckhage

All text-based language problems can be reduced to either generation or embedding. Current models only perform well at one or the other. We introduce generative representational instruction tuning (GRIT) whereby a large language model is…

计算与语言 · 计算机科学 2025-03-04 Niklas Muennighoff , Hongjin Su , Liang Wang , Nan Yang , Furu Wei , Tao Yu , Amanpreet Singh , Douwe Kiela

We present Sounding Board, a social chatbot that won the 2017 Amazon Alexa Prize. The system architecture consists of several components including spoken language processing, dialogue management, language generation, and content management,…

人机交互 · 计算机科学 2018-04-30 Hao Fang , Hao Cheng , Maarten Sap , Elizabeth Clark , Ari Holtzman , Yejin Choi , Noah A. Smith , Mari Ostendorf

Semantic grasping is the problem of selecting stable grasps that are functionally suitable for specific object manipulation tasks. In order for robots to effectively perform object manipulation, a broad sense of contexts, including object…

机器人学 · 计算机科学 2020-06-09 Weiyu Liu , Angel Daruna , Sonia Chernova

Despite significant advancements in robotic manipulation, achieving consistent and stable grasping remains a fundamental challenge, often limiting the successful execution of complex tasks. Our analysis reveals that even state-of-the-art…

人工智能 · 计算机科学 2025-03-20 Sungjae Lee , Yeonjoo Hong , Kwang In Kim

This paper presents a Generative RegIon-to-Text transformer, GRiT, for object understanding. The spirit of GRiT is to formulate object understanding as <region, text> pairs, where region locates objects and text describes objects. For…

计算机视觉与模式识别 · 计算机科学 2022-12-02 Jialian Wu , Jianfeng Wang , Zhengyuan Yang , Zhe Gan , Zicheng Liu , Junsong Yuan , Lijuan Wang

Agentic LLM frameworks that rely on prompted orchestration, where the model itself determines workflow transitions, often suffer from hallucinated routing, infinite loops, and non-reproducible execution. We introduce GraphBit, an…

人工智能 · 计算机科学 2026-05-15 Yeahia Sarker , Md Rahmat Ullah , Musa Molla , Shafiq Joty

Recent years have seen an increasing number of applications that have a natural language interface, either in the form of chatbots or via personal assistants such as Alexa (Amazon), Google Assistant, Siri (Apple), and Cortana (Microsoft).…

计算与语言 · 计算机科学 2022-05-26 Avichai Levy , Erez Karpas

This paper describes the Tartan conversational agent built for the 2018 Alexa Prize Competition. Tartan is a non-goal-oriented socialbot focused around providing users with an engaging and fluent casual conversation. Tartan's key features…

Smartphones have significantly enhanced our daily learning, communication, and entertainment, becoming an essential component of modern life. However, certain populations, including the elderly and individuals with disabilities, encounter…

机器人学 · 计算机科学 2024-09-17 Kelin Fu , Yang Tian , Kaigui Bian

Graphical User Interface (GUI) automation holds significant promise for assisting users with complex tasks, thereby boosting human productivity. Existing works leveraging Large Language Model (LLM) or LLM-based AI agents have shown…

计算机视觉与模式识别 · 计算机科学 2024-01-02 Difei Gao , Lei Ji , Zechen Bai , Mingyu Ouyang , Peiran Li , Dongxing Mao , Qinchen Wu , Weichen Zhang , Peiyi Wang , Xiangwu Guo , Hengxu Wang , Luowei Zhou , Mike Zheng Shou

Large language models (LLMs) have emerged as the dominant paradigm for robotic task planning using natural language instructions. However, trained on general internet data, LLMs are not inherently aligned with the embodiment, skill sets,…