Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Teo, Choon Hui"'
Large Language Models (LLMs) have seen widespread adoption due to their remarkable natural language capabilities. However, when deploying them in real-world settings, it is important to align LLMs to generate texts according to acceptable human stand
Externí odkaz:
http://arxiv.org/abs/2407.06443
Autor:
Chang, Wei-Cheng, Jiang, Jyun-Yu, Zhang, Jiong, Al-Darabsah, Mutasem, Teo, Choon Hui, Hsieh, Cho-Jui, Yu, Hsiang-Fu, Vishwanathan, S. V. N.
Embedding-based Retrieval Models (ERMs) have emerged as a promising framework for large-scale text retrieval problems due to powerful large language models. Nevertheless, fine-tuning ERMs to reach state-of-the-art results can be expensive due to the
Externí odkaz:
http://arxiv.org/abs/2312.02429
Publikováno v:
Proceedings of the 29th International Conference on Computational Linguistics (COLING). 2022
In contrast to traditional exhaustive search, selective search first clusters documents into several groups before all the documents are searched exhaustively by a query, to limit the search executed within one group or only a few groups. Selective s
Externí odkaz:
http://arxiv.org/abs/2209.04378
Autor:
Jiang, Nan, Eswaran, Dhivya, Teo, Choon Hui, Xue, Yexiang, Dattatreya, Yesh, Sanghavi, Sujay, Vishwanathan, Vishy
We consider text retrieval within dense representational space in real-world settings such as e-commerce search where (a) document popularity and (b) diversity of queries associated with a document have a skewed distribution. Most of the contemporary
Externí odkaz:
http://arxiv.org/abs/2208.05663
Autor:
Lakshman, Vihan, Teo, Choon Hui, Chu, Xiaowen, Nigam, Priyanka, Patni, Abhinandan, Maknikar, Pooja, Vishwanathan, SVN
We present principled approaches to train and deploy dyadic neural embedding models at the billion scale, focusing our investigation on the application of semantic product search. When training a dyadic model, one seeks to embed two different types o
Externí odkaz:
http://arxiv.org/abs/2110.06125
Autor:
Chang, Wei-Cheng, Jiang, Daniel, Yu, Hsiang-Fu, Teo, Choon-Hui, Zhang, Jiong, Zhong, Kai, Kolluri, Kedarnath, Hu, Qie, Shandilya, Nikhil, Ievgrafov, Vyacheslav, Singh, Japinder, Dhillon, Inderjit S.
We consider the problem of semantic matching in product search: given a customer query, retrieve all semantically related products from a huge catalog of size 100 million, or more. Because of large catalog spaces and real-time latency constraints, se
Externí odkaz:
http://arxiv.org/abs/2106.12657
In product search, users tend to browse results on multiple search result pages (SERPs) (e.g., for queries on clothing and shoes) before deciding which item to purchase. Users' clicks can be considered as implicit feedback which indicates their prefe
Externí odkaz:
http://arxiv.org/abs/1909.04031
Product search serves as an important entry point for online shopping. In contrast to web search, the retrieved results in product search not only need to be relevant but also should satisfy customers' preferences in order to elicit purchases. Previo
Externí odkaz:
http://arxiv.org/abs/1909.02065
Autor:
Nigam, Priyanka, Song, Yiwei, Mohan, Vijai, Lakshman, Vihan, Weitian, Ding, Shingavi, Ankit, Teo, Choon Hui, Gu, Hao, Yin, Bing
We study the problem of semantic matching in product search, that is, given a customer query, retrieve all semantically related products from the catalog. Pure lexical matching via an inverted index falls short in this respect due to several factors:
Externí odkaz:
http://arxiv.org/abs/1907.00937
Autor:
Teo, Choon Hui, Nassif, Houssam, Hill, Daniel, Srinavasan, Sriram, Goodman, Mitchell, Mohan, Vijai, Vishwanathan, SVN
Publikováno v:
Adaptive, Personalized Diversity for Visual Discovery. Teo CH, Nassif H, Hill D, Srinavasan S, Goodman M, Mohan V, and Vishwanathan SVN. ACM Conference on Recommender Systems (RecSys'16), Boston, pp. 35-38, 2016
Search queries are appropriate when users have explicit intent, but they perform poorly when the intent is difficult to express or if the user is simply looking to be inspired. Visual browsing systems allow e-commerce platforms to address these scena
Externí odkaz:
http://arxiv.org/abs/1810.01477