200 citations · 274 across the 6 of their papers we have counts for
6 papers
KUDA: Knowledge Unlearning by Deviating Representation for Large Language Models
Ce Fang, Zhikun Zhang, Min Chen +4
Large language models (LLMs) acquire a large amount of knowledge through pre-training on vast and diverse corpora. While this endows LLMs with strong capabilities in generation and…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
HierCat: Hierarchical Query Categorization from Weakly Supervised Data at Facebook Marketplace
Yunzhong He, Cong Zhang, Ruoyan Kong +5
Query categorization at customer-to-customer e-commerce platforms like Facebook Marketplace is challenging due to the vagueness of search intent, noise in real-world data, and imba…
Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems
Anish Acharya, Suranjit Adhikari, Sanchit Agarwal +28
Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Trai…
Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh +19
Building open domain conversational systems that allow users to have engaging conversations on topics of their choice is a challenging task. Alexa Prize was launched in 2016 to tac…
Conversational AI: The Science Behind the Alexa Prize
Ashwin Ram, Rohit Prasad, Chandra Khatri +15
Conversational agents are exploding in popularity. However, much work remains in the area of social conversation as well as free-form conversation over a broad range of domains and…