1 citations · 1 across the 5 of their papers we have counts for
5 papers
Are LLMs Positionally Consistent Ordinal Classifiers? A Systematic Evaluation
Yu Wang, Zhe Zhou, Menglin Liu +1
Large language models are increasingly used for ordinal classification, yet semantically equivalent changes to prompt organization can alter their predictions. We conduct systemati…
Long-Horizon Plan Execution in Large Tool Spaces through Entropy-Guided Branching
Rongzhe Wei, Ge Shi, Min Cheng +5
Large Language Models (LLMs) have significantly advanced tool-augmented agents, enabling autonomous reasoning via API interactions. However, executing multi-step tasks within massi…
Long Story Generation via Knowledge Graph and Literary Theory
Ge Shi, Kaiyu Huang, Guochen Feng
The generation of a long story consisting of several thousand words is a sub-task in the field of long text generation~(LTG). Previous research has addressed this challenge through…
Enhancing LLM-Based Text Classification in Political Science: Automatic Prompt Optimization and Dynamic Exemplar Selection for Few-Shot Learning
Menglin Liu, Ge Shi
Large language models (LLMs) offer substantial promise for text classification in political science, yet their effectiveness often depends on high-quality prompts and exemplars. To…
RAAMove: A Corpus for Analyzing Moves in Research Article Abstracts
Hongzheng Li, Ruojin Wang, Ge Shi +7
Move structures have been studied in English for Specific Purposes (ESP) and English for Academic Purposes (EAP) for decades. However, there are few move annotation corpora for Res…