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20212024
most citedKitchenScale: Learning to predict ingredient quantities from recipe contexts

12 citations · 27 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CL2024

LAPIS: Language Model-Augmented Police Investigation System

Heedou Kim, Dain Kim, Jiwoo Lee +4

Crime situations are race against time. An AI-assisted criminal investigation system, providing prompt but precise legal counsel is in need for police officers. We introduce LAPIS…

cs.CL20234 cited

Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models

Gangwoo Kim, Sungdong Kim, Byeongguk Jeon +2

Questions in open-domain question answering are often ambiguous, allowing multiple interpretations. One approach to handling them is to identify all possible interpretations of the…

cs.CL202312 cited

KitchenScale: Learning to predict ingredient quantities from recipe contexts

Donghee Choi, Mogan Gim, Samy Badreddine +3

Determining proper quantities for ingredients is an essential part of cooking practice from the perspective of enriching tastiness and promoting healthiness. We introduce KitchenSc…

cs.CL20232 cited

LIQUID: A Framework for List Question Answering Dataset Generation

Seongyun Lee, Hyunjae Kim, Jaewoo Kang

Question answering (QA) models often rely on large-scale training datasets, which necessitates the development of a data generation framework to reduce the cost of manual annotatio…

cs.CL2022

Lack of Fluency is Hurting Your Translation Model

Jaehyo Yoo, Jaewoo Kang

Many machine translation models are trained on bilingual corpus, which consist of aligned sentence pairs from two different languages with same semantic. However, there is a qualit…

cs.CL20211 cited

Can Language Models be Biomedical Knowledge Bases?

Mujeen Sung, Jinhyuk Lee, Sean Yi +3

Pre-trained language models (LMs) have become ubiquitous in solving various natural language processing (NLP) tasks. There has been increasing interest in what knowledge these LMs…