12 citations · 24 across the 10 of their papers we have counts for
10 papers
An LLM-based Chain-of-Response Counter-Scam System
Heedou Kim, Mogan Gim, Donghee Choi +4
The rapid evolution of online scams, driven by transnational networks and mass produced social engineering scenarios, has exposed the speed limitations of conventional detection, n…
DeepAries: Adaptive Rebalancing Interval Selection for Enhanced Portfolio Selection
Jinkyu Kim, Hyunjung Yi, Mogan Gim +2
We propose DeepAries , a novel deep reinforcement learning framework for dynamic portfolio management that jointly optimizes the timing and allocation of rebalancing decisions. Unl…
Culinary Class Wars: Evaluating LLMs using ASH in Cuisine Transfer Task
Hoonick Lee, Mogan Gim, Donghyeon Park +2
The advent of Large Language Models (LLMs) have shown promise in various creative domains, including culinary arts. However, many LLMs still struggle to deliver the desired level o…
DeepClair: Utilizing Market Forecasts for Effective Portfolio Selection
Donghee Choi, Jinkyu Kim, Mogan Gim +2
Utilizing market forecasts is pivotal in optimizing portfolio selection strategies. We introduce DeepClair, a novel framework for portfolio selection. DeepClair leverages a transfo…
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…
CookingSense: A Culinary Knowledgebase with Multidisciplinary Assertions
Donghee Choi, Mogan Gim, Donghyeon Park +4
This paper introduces CookingSense, a descriptive collection of knowledge assertions in the culinary domain extracted from various sources, including web data, scientific papers, a…
Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks
Hyunjae Kim, Hyeon Hwang, Jiwoo Lee +7
While recent advancements in commercial large language models (LM) have shown promising results in medical tasks, their closed-source nature poses significant privacy and security…
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…
RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer
Mogan Gim, Donghee Choi, Kana Maruyama +4
We propose a computational approach for recipe ideation, a downstream task that helps users select and gather ingredients for creating dishes. To perform this task, we developed Re…
Learning User Preferences and Understanding Calendar Contexts for Event Scheduling
Donghyeon Kim, Jinhyuk Lee, Donghee Choi +2
With online calendar services gaining popularity worldwide, calendar data has become one of the richest context sources for understanding human behavior. However, event scheduling…