no code implementations • 14 Mar 2025 • Kun Su, Krishna Sayana, Hubert Pham, James Pine, Yuri Vasilevski, Raghavendra Vasudeva, Marialena Kyriakidi, Liam Hebert, Ambarish Jash, Anushya Subbiah, Sukhdeep Sodhi
Further, we establish an end-to-end modeling benchmark for the task of conversational recommendation, where models are trained to generate both recommendations and corresponding narratives conditioned on user history (items and critiques).
no code implementations • 22 Oct 2024 • Krishna Sayana, Raghavendra Vasudeva, Yuri Vasilevski, Kun Su, Liam Hebert, James Pine, Hubert Pham, Ambarish Jash, Sukhdeep Sodhi
And to the best of our knowledge, represents the first attempt to analyze the capabilities of LLMs in understanding recommender signals and generating rich narratives.
no code implementations • 18 Sep 2024 • Liam Hebert, Marialena Kyriakidi, Hubert Pham, Krishna Sayana, James Pine, Sukhdeep Sodhi, Ambarish Jash
With revised baselines for item ID-only models, this paper also establishes new competitive results for architectures that combine IDs and textual descriptions.
no code implementations • 2 Aug 2024 • Liam Hebert, Krishna Sayana, Ambarish Jash, Alexandros Karatzoglou, Sukhdeep Sodhi, Sumanth Doddapaneni, Yanli Cai, Dima Kuzmin
Understanding the nuances of a user's extensive interaction history is key to building accurate and personalized natural language systems that can adapt to evolving user preferences.
no code implementations • 10 Jan 2024 • Sumanth Doddapaneni, Krishna Sayana, Ambarish Jash, Sukhdeep Sodhi, Dima Kuzmin
Modeling long histories plays a pivotal role in enhancing recommendation systems, allowing to capture user's evolving preferences, resulting in more precise and personalized recommendations.
no code implementations • 6 Jul 2023 • Abhirut Gupta, Ananya B. Sai, Richard Sproat, Yuri Vasilevski, James S. Ren, Ambarish Jash, Sukhdeep S. Sodhi, Aravindan Raghuveer
To the best of our knowledge, FunGLUE is the first benchmark to introduce L1-L2 interactions in text.
no code implementations • 8 May 2023 • Naveen Ram, Dima Kuzmin, Ellie Ka In Chio, Moustafa Farid Alzantot, Santiago Ontanon, Ambarish Jash, Judith Yue Li
In this paper, we analyze the performance of a multitask end-to-end transformer model on the task of conversational recommendations, which aim to provide recommendations based on a user's explicit preferences expressed in dialogue.
no code implementations • 20 May 2021 • Sukhdeep S. Sodhi, Ellie Ka-In Chio, Ambarish Jash, Santiago Ontañón, Ajit Apte, Ankit Kumar, Ayooluwakunmi Jeje, Dima Kuzmin, Harry Fung, Heng-Tze Cheng, Jon Effrat, Tarush Bali, Nitin Jindal, Pei Cao, Sarvjeet Singh, Senqiang Zhou, Tameen Khan, Amol Wankhede, Moustafa Alzantot, Allen Wu, Tushar Chandra
As more and more online search queries come from voice, automatic speech recognition becomes a key component to deliver relevant search results.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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