4 citations · 6 across the 8 of their papers we have counts for
8 papers
Small Language Models Need Strong Verifiers to Self-Correct Reasoning
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran +4
Self-correction has emerged as a promising solution to boost the reasoning performance of large language models (LLMs), where LLMs refine their solutions using self-generated criti…
Merging Generated and Retrieved Knowledge for Open-Domain QA
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran +3
Open-domain question answering (QA) systems are often built with retrieval modules. However, retrieving passages from a given source is known to suffer from insufficient knowledge…
Investigating Zero- and Few-shot Generalization in Fact Verification
Liangming Pan, Yunxiang Zhang, Min-Yen Kan
In this paper, we explore zero- and few-shot generalization for fact verification (FV), which aims to generalize the FV model trained on well-resourced domains (e.g., Wikipedia) to…
SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning
Yunxiang Zhang, Xiaojun Wan
Recently, commonsense reasoning in text generation has attracted much attention. Generative commonsense reasoning is the task that requires machines, given a group of keywords, to…
CC-Riddle: A Question Answering Dataset of Chinese Character Riddles
Fan Xu, Yunxiang Zhang, Xiaojun Wan
The Chinese character riddle is a unique form of cultural entertainment specific to the Chinese language. It typically comprises two parts: the riddle description and the solution.…
Interpreting the Robustness of Neural NLP Models to Textual Perturbations
Yunxiang Zhang, Liangming Pan, Samson Tan +1
Modern Natural Language Processing (NLP) models are known to be sensitive to input perturbations and their performance can decrease when applied to real-world, noisy data. However,…
BiRdQA: A Bilingual Dataset for Question Answering on Tricky Riddles
Yunxiang Zhang, Xiaojun Wan
A riddle is a question or statement with double or veiled meanings, followed by an unexpected answer. Solving riddle is a challenging task for both machine and human, testing the c…
MOVER: Mask, Over-generate and Rank for Hyperbole Generation
Yunxiang Zhang, Xiaojun Wan
Despite being a common figure of speech, hyperbole is under-researched in Figurative Language Processing. In this paper, we tackle the challenging task of hyperbole generation to t…