activity
20192025
most citedTask Contamination: Language Models May Not Be Few-Shot Anymore

6 citations · 20 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2025

A Large-scale Dataset for Robust Complex Anime Scene Text Detection

Ziyi Dong, Yurui Zhang, Changmao Li +2

Current text detection datasets primarily target natural or document scenes, where text typically appear in regular font and shapes, monotonous colors, and orderly layouts. The tex…

cs.CL2025

Trace Is In Sentences: Unbiased Lightweight ChatGPT-Generated Text Detector

Mo Mu, Dianqiao Lei, Chang Li

The widespread adoption of ChatGPT has raised concerns about its misuse, highlighting the need for robust detection of AI-generated text. Current word-level detectors are vulnerabl…

cs.CL2024

RAC: Efficient LLM Factuality Correction with Retrieval Augmentation

Changmao Li, Jeffrey Flanigan

Large Language Models (LLMs) exhibit impressive results across a wide range of natural language processing (NLP) tasks, yet they can often produce factually incorrect outputs. This…

cs.CL2024

Future Language Modeling from Temporal Document History

Changmao Li, Jeffrey Flanigan

Predicting the future is of great interest across many aspects of human activity. Businesses are interested in future trends, traders are interested in future stock prices, and com…

cs.CL2023★ 6 cited

Task Contamination: Language Models May Not Be Few-Shot Anymore

Changmao Li, Jeffrey Flanigan

Large language models (LLMs) offer impressive performance in various zero-shot and few-shot tasks. However, their success in zero-shot and few-shot settings may be affected by task…

cs.CL2020★ 1 cited

Competence-Level Prediction and Resume & Job Description Matching Using Context-Aware Transformer Models

Changmao Li, Elaine Fisher, Rebecca Thomas +3

This paper presents a comprehensive study on resume classification to reduce the time and labor needed to screen an overwhelming number of applications significantly, while improvi…

cs.CL2020★ 6 cited

Transformers to Learn Hierarchical Contexts in Multiparty Dialogue for Span-based Question Answering

Changmao Li, Jinho D. Choi

We introduce a novel approach to transformers that learns hierarchical representations in multiparty dialogue. First, three language modeling tasks are used to pre-train the transf…

cs.CL2020★ 5 cited

Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media

Xiangjue Dong, Changmao Li, Jinho D. Choi

We present a transformer-based sarcasm detection model that accounts for the context from the entire conversation thread for more robust predictions. Our model uses deep transforme…

cs.AI2019

Challenging On Car Racing Problem from OpenAI gym

Changmao Li

This project challenges the car racing problem from OpenAI gym environment. The problem is very challenging since it requires computer to finish the continuous control task by lear…

cs.LG2019★ 1 cited

Ten-year Survival Prediction for Breast Cancer Patients

Changmao Li, Han He, Yunze Hao +1

This report assesses different machine learning approaches to 10-year survival prediction of breast cancer patients.

cs.CL2019★ 1 cited

Design and Challenges of Cloze-Style Reading Comprehension Tasks on Multiparty Dialogue

Changmao Li, Tianhao Liu, Jinho D. Choi

This paper analyzes challenges in cloze-style reading comprehension on multiparty dialogue and suggests two new tasks for more comprehensive predictions of personal entities in dai…