198 citations · 562 across the 31 of their papers we have counts for
10 papers · 1 filter
P^3SUM: Preserving Author's Perspective in News Summarization with Diffusion Language Models
Yuhan Liu, Shangbin Feng, Xiaochuang Han +4
In this work, we take a first step towards designing summarization systems that are faithful to the author's intent, not only the semantic content of the article. Focusing on a cas…
KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Models
Yuyang Bai, Shangbin Feng, Vidhisha Balachandran +4
Large language models (LLMs) demonstrate remarkable performance on knowledge-intensive tasks, suggesting that real-world knowledge is encoded in their model parameters. However, be…
Resolving Knowledge Conflicts in Large Language Models
Yike Wang, Shangbin Feng, Heng Wang +4
Large language models (LLMs) often encounter knowledge conflicts, scenarios where discrepancy arises between the internal parametric knowledge of LLMs and non-parametric informatio…
Can Language Models Solve Graph Problems in Natural Language?
Heng Wang, Shangbin Feng, Tianxing He +3
Large language models (LLMs) are increasingly adopted for a variety of tasks with implicit graphical structures, such as planning in robotics, multi-hop question answering or knowl…
Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models
Shangbin Feng, Weijia Shi, Yuyang Bai +3
By design, large language models (LLMs) are static general-purpose models, expensive to retrain or update frequently. As they are increasingly adopted for knowledge-intensive tasks…
From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
Shangbin Feng, Chan Young Park, Yuhan Liu +1
Language models (LMs) are pretrained on diverse data sources, including news, discussion forums, books, and online encyclopedias. A significant portion of this data includes opinio…
FactKB: Generalizable Factuality Evaluation using Language Models Enhanced with Factual Knowledge
Shangbin Feng, Vidhisha Balachandran, Yuyang Bai +1
Evaluating the factual consistency of automatically generated summaries is essential for the progress and adoption of reliable summarization systems. Despite recent advances, exist…
BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts
Yuhan Liu, Zhaoxuan Tan, Heng Wang +3
Twitter bot detection has become a crucial task in efforts to combat online misinformation, mitigate election interference, and curb malicious propaganda. However, advanced Twitter…
Detecting Spoilers in Movie Reviews with External Movie Knowledge and User Networks
Heng Wang, Wenqian Zhang, Yuyang Bai +4
Online movie review platforms are providing crowdsourced feedback for the film industry and the general public, while spoiler reviews greatly compromise user experience. Although p…
BotPercent: Estimating Bot Populations in Twitter Communities
Zhaoxuan Tan, Shangbin Feng, Melanie Sclar +4
Twitter bot detection is vital in combating misinformation and safeguarding the integrity of social media discourse. While malicious bots are becoming more and more sophisticated a…