8 citations · 21 across the 10 of their papers we have counts for
10 papers
Which Questions Improve Learning the Most? Utility Estimation of Questions with LM-based Simulations
Dong-Ho Lee, Hyundong Cho, Jonathan May +1
Asking good questions is critical for comprehension and learning, yet evaluating and generating such questions remains a challenging problem. Prior work on inquisitive questions fo…
Integrating Pre-Trained Language Model with Physical Layer Communications
Ju-Hyung Lee, Dong-Ho Lee, Joohan Lee +1
The burgeoning field of on-device AI communication, where devices exchange information directly through embedded foundation models, such as language models (LMs), requires robust,…
Making Large Language Models Better Data Creators
Dong-Ho Lee, Jay Pujara, Mohit Sewak +2
Although large language models (LLMs) have advanced the state-of-the-art in NLP significantly, deploying them for downstream applications is still challenging due to cost, responsi…
Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning
Dong-Ho Lee, Kian Ahrabian, Woojeong Jin +2
Temporal knowledge graph (TKG) forecasting benchmarks challenge models to predict future facts using knowledge of past facts. In this paper, we apply large language models (LLMs) t…
Seq2Seq-SC: End-to-End Semantic Communication Systems with Pre-trained Language Model
Ju-Hyung Lee, Dong-Ho Lee, Eunsoo Sheen +2
In this work, we propose a realistic semantic network called seq2seq-SC, designed to be compatible with 5G NR and capable of working with generalized text datasets using a pre-trai…
Perhaps PTLMs Should Go to School -- A Task to Assess Open Book and Closed Book QA
Manuel R. Ciosici, Joe Cecil, Alex Hedges +3
Our goal is to deliver a new task and leaderboard to stimulate research on question answering and pre-trained language models (PTLMs) to understand a significant instructional docu…
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER
Dong-Ho Lee, Akshen Kadakia, Kangmin Tan +7
Recent advances in prompt-based learning have shown strong results on few-shot text classification by using cloze-style templates. Similar attempts have been made on named entity r…
Improving Text Auto-Completion with Next Phrase Prediction
Dong-Ho Lee, Zhiqiang Hu, Roy Ka-Wei Lee
Language models such as GPT-2 have performed well on constructing syntactically sound sentences for text auto-completion task. However, such models often require considerable train…
RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge
Bill Yuchen Lin, Ziyi Wu, Yichi Yang +2
Question: I have five fingers but I am not alive. What am I? Answer: a glove. Answering such a riddle-style question is a challenging cognitive process, in that it requires complex…
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data
Woojeong Jin, Rahul Khanna, Suji Kim +4
Event forecasting is a challenging, yet important task, as humans seek to constantly plan for the future. Existing automated forecasting studies rely mostly on structured data, suc…