565 citations · 654 across the 13 of their papers we have counts for
15 papers
Avoiding Copyright Infringement via Large Language Model Unlearning
Guangyao Dou, Zheyuan Liu, Qing Lyu +2
Pre-trained Large Language Models (LLMs) have demonstrated remarkable capabilities but also pose risks by learning and generating copyrighted material, leading to significant legal…
Calibrating Large Language Models with Sample Consistency
Qing Lyu, Kumar Shridhar, Chaitanya Malaviya +6
Accurately gauging the confidence level of Large Language Models' (LLMs) predictions is pivotal for their reliable application. However, LLMs are often uncalibrated inherently and…
Interpretable-by-Design Text Understanding with Iteratively Generated Concept Bottleneck
Josh Magnus Ludan, Qing Lyu, Yue Yang +3
Black-box deep neural networks excel in text classification, yet their application in high-stakes domains is hindered by their lack of interpretability. To address this, we propose…
Explanation-based Finetuning Makes Models More Robust to Spurious Cues
Josh Magnus Ludan, Yixuan Meng, Tai Nguyen +4
Large Language Models (LLMs) are so powerful that they sometimes learn correlations between labels and features that are irrelevant to the task, leading to poor generalization on o…
Representation Of Lexical Stylistic Features In Language Models' Embedding Space
Qing Lyu, Marianna Apidianaki, Chris Callison-Burch
The representation space of pretrained Language Models (LMs) encodes rich information about words and their relationships (e.g., similarity, hypernymy, polysemy) as well as abstrac…
M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models
Chuang Liu, Renren Jin, Yuqi Ren +10
Large language models have recently made tremendous progress in a variety of aspects, e.g., cross-task generalization, instruction following. Comprehensively evaluating the capabil…
Faithful Chain-of-Thought Reasoning
Qing Lyu, Shreya Havaldar, Adam Stein +5
While Chain-of-Thought (CoT) prompting boosts Language Models' (LM) performance on a gamut of complex reasoning tasks, the generated reasoning chain does not necessarily reflect ho…
Towards Faithful Model Explanation in NLP: A Survey
Qing Lyu, Marianna Apidianaki, Chris Callison-Burch
End-to-end neural Natural Language Processing (NLP) models are notoriously difficult to understand. This has given rise to numerous efforts towards model explainability in recent y…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
Show Me More Details: Discovering Hierarchies of Procedures from Semi-structured Web Data
Shuyan Zhou, Li Zhang, Yue Yang +4
Procedures are inherently hierarchical. To "make videos", one may need to "purchase a camera", which in turn may require one to "set a budget". While such hierarchical knowledge is…
Is "My Favorite New Movie" My Favorite Movie? Probing the Understanding of Recursive Noun Phrases
Qing Lyu, Hua Zheng, Daoxin Li +3
Recursive noun phrases (NPs) have interesting semantic properties. For example, "my favorite new movie" is not necessarily my favorite movie, whereas "my new favorite movie" is. Th…
Goal-Oriented Script Construction
Qing Lyu, Li Zhang, Chris Callison-Burch
The knowledge of scripts, common chains of events in stereotypical scenarios, is a valuable asset for task-oriented natural language understanding systems. We propose the Goal-Orie…
Visual Goal-Step Inference using wikiHow
Yue Yang, Artemis Panagopoulou, Qing Lyu +3
Understanding what sequence of steps are needed to complete a goal can help artificial intelligence systems reason about human activities. Past work in NLP has examined the task of…
Reasoning about Goals, Steps, and Temporal Ordering with WikiHow
Li Zhang, Qing Lyu, Chris Callison-Burch
We propose a suite of reasoning tasks on two types of relations between procedural events: goal-step relations ("learn poses" is a step in the larger goal of "doing yoga") and step…
Intent Detection with WikiHow
Li Zhang, Qing Lyu, Chris Callison-Burch
Modern task-oriented dialog systems need to reliably understand users' intents. Intent detection is most challenging when moving to new domains or new languages, since there is lit…