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20192025
most citedTransformers to Learn Hierarchical Contexts in Multiparty Dialogue for Span-based Question Answering

6 citations · 13 across the 7 of their papers we have counts for

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5 papers · 1 filter

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.CL20201 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.CL20206 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.CL20205 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…