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20222026
most citedWhen does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks

5 citations · 12 across the 22 of their papers we have counts for

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Showing 2024 · cs.CLShow all

6 papers · 2 filters

cs.CL2024

Template-Driven LLM-Paraphrased Framework for Tabular Math Word Problem Generation

Xiaoqiang Kang, Zimu Wang, Xiaobo Jin +3

Solving tabular math word problems (TMWPs) has become a critical role in evaluating the mathematical reasoning ability of large language models (LLMs), where large-scale TMWP sampl…

cs.CL2024

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

Jiayuan Ma, Hongbin Na, Zimu Wang +4

Mental manipulation severely undermines mental wellness by covertly and negatively distorting decision-making. While there is an increasing interest in mental health care within th…

cs.CL2024

Domain-specific Guided Summarization for Mental Health Posts

Lu Qian, Yuqi Wang, Zimu Wang +4

In domain-specific contexts, particularly mental health, abstractive summarization requires advanced techniques adept at handling specialized content to generate domain-relevant an…

cs.CL2024

Guardians of Discourse: Evaluating LLMs on Multilingual Offensive Language Detection

Jianfei He, Lilin Wang, Jiaying Wang +5

Identifying offensive language is essential for maintaining safety and sustainability in the social media era. Though large language models (LLMs) have demonstrated encouraging pot…

cs.CL2024

Document-level Causal Relation Extraction with Knowledge-guided Binary Question Answering

Zimu Wang, Lei Xia, Wei Wang +1

As an essential task in information extraction (IE), Event-Event Causal Relation Extraction (ECRE) aims to identify and classify the causal relationships between event mentions in…

cs.CL2024

Thinker-DDM: Modeling Deliberation for Machine Translation with a Drift-Diffusion Process

Hongbin Na, Zimu Wang, Mieradilijiang Maimaiti +4

Large language models (LLMs) have demonstrated promising potential in various downstream tasks, including machine translation. However, prior work on LLM-based machine translation…