7 citations · 15 across the 12 of their papers we have counts for
13 papers
AutoLexSteer: Automatic Contrast Construction for Lexical Activation Steering
Shuhe Wang, Lachlan Cowley, Eduard Hovy +1
Steering vectors have rapidly emerged as a popular and effective method for guiding the output of LLMs in very specific ways. But constructing accurate steering vectors is a diffic…
Retain or Reframe? A Computational Framework for the Analysis of Framing in News Articles and Reader Comments
Matteo Guida, Yulia Otmakhova, Eduard Hovy +1
When a news article describes immigration as an "economic burden" or a "humanitarian crisis," it selectively emphasizes certain aspects of the issue. Although \textit{framing} shap…
LLMs for Argument Mining: Detection, Extraction, and Relationship Classification of pre-defined Arguments in Online Comments
Matteo Guida, Yulia Otmakhova, Eduard Hovy +1
Automated large-scale analysis of public discussions around contested issues like abortion requires detecting and understanding the use of arguments. While Large Language Models (L…
FaceID-6M: A Large-Scale, Open-Source FaceID Customization Dataset
Shuhe Wang, Xiaoya Li, Jiwei Li +8
Due to the data-driven nature of current face identity (FaceID) customization methods, all state-of-the-art models rely on large-scale datasets containing millions of high-quality…
Rumor Detection by Multi-task Suffix Learning based on Time-series Dual Sentiments
Zhiwei Liu, Kailai Yang, Eduard Hovy +1
The widespread dissemination of rumors on social media has a significant impact on people's lives, potentially leading to public panic and fear. Rumors often evoke specific sentime…
Turn That Frown Upside Down: FaceID Customization via Cross-Training Data
Shuhe Wang, Xiaoya Li, Xiaofei Sun +4
Existing face identity (FaceID) customization methods perform well but are limited to generating identical faces as the input, while in real-world applications, users often desire…
Decomposed Opinion Summarization with Verified Aspect-Aware Modules
Miao Li, Jey Han Lau, Eduard Hovy +1
Opinion summarization plays a key role in deriving meaningful insights from large-scale online reviews. To make the process more explainable and grounded, we propose a domain-agnos…
Reinforcement Learning Enhanced LLMs: A Survey
Shuhe Wang, Shengyu Zhang, Jie Zhang +7
Reinforcement learning (RL) enhanced large language models (LLMs), particularly exemplified by DeepSeek-R1, have exhibited outstanding performance. Despite the effectiveness in imp…
Packing Analysis: Packing Is More Appropriate for Large Models or Datasets in Supervised Fine-tuning
Shuhe Wang, Guoyin Wang, Yizhong Wang +3
Packing, initially utilized in the pre-training phase, is an optimization technique designed to maximize hardware resource efficiency by combining different training sequences to f…
RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Information
Zhiwei Liu, Kailai Yang, Qianqian Xie +3
Misinformation is prevalent in various fields such as education, politics, health, etc., causing significant harm to society. However, current methods for cross-domain misinformati…
BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models
Jacek Wiland, Max Ploner, Alan Akbik
Knowledge probing assesses to which degree a language model (LM) has successfully learned relational knowledge during pre-training. Probing is an inexpensive way to compare LMs of…
A Sentiment Consolidation Framework for Meta-Review Generation
Miao Li, Jey Han Lau, Eduard Hovy
Modern natural language generation systems with Large Language Models (LLMs) exhibit the capability to generate a plausible summary of multiple documents; however, it is uncertain…
Sim-GPT: Text Similarity via GPT Annotated Data
Shuhe Wang, Beiming Cao, Shengyu Zhang +5
Due to the lack of a large collection of high-quality labeled sentence pairs with textual similarity scores, existing approaches for Semantic Textual Similarity (STS) mostly rely o…