5 papers · 1 filter
WhoSaidIt: Human-LLM Collaborative Annotation for Text-Based Multilingual Speaker-Attribute Classification
Lingyu Gao, Will Monroe, David Smith +2
Annotating speaker attributes from text is inherently ambiguous, particularly in multilingual settings where demographic and social cues are implicit and culturally variable. We pr…
Harnessing the Intrinsic Knowledge of Pretrained Language Models for Challenging Text Classification Settings
Lingyu Gao
Text classification is crucial for applications such as sentiment analysis and toxic text filtering, but it still faces challenges due to the complexity and ambiguity of natural la…
Ambiguity-Aware In-Context Learning with Large Language Models
Lingyu Gao, Aditi Chaudhary, Krishna Srinivasan +3
In-context learning (ICL) i.e. showing LLMs only a few task-specific demonstrations has led to downstream gains with no task-specific fine-tuning required. However, LLMs are sensit…
"What makes a question inquisitive?" A Study on Type-Controlled Inquisitive Question Generation
Lingyu Gao, Debanjan Ghosh, Kevin Gimpel
We propose a type-controlled framework for inquisitive question generation. We annotate an inquisitive question dataset with question types, train question type classifiers, and fi…
A Cross-Task Analysis of Text Span Representations
Shubham Toshniwal, Haoyue Shi, Bowen Shi +3
Many natural language processing (NLP) tasks involve reasoning with textual spans, including question answering, entity recognition, and coreference resolution. While extensive res…