80 citations · 297 across the 46 of their papers we have counts for
9 papers · 1 filter
Constraint Back-translation Improves Complex Instruction Following of Large Language Models
Yunjia Qi, Hao Peng, Xiaozhi Wang +3
Large language models (LLMs) struggle to follow instructions with complex constraints in format, length, etc. Following the conventional instruction-tuning practice, previous works…
Configurable Foundation Models: Building LLMs from a Modular Perspective
Chaojun Xiao, Zhengyan Zhang, Chenyang Song +20
Advancements in LLMs have recently unveiled challenges tied to computational efficiency and continual scalability due to their requirements of huge parameters, making the applicati…
OpenEP: Open-Ended Future Event Prediction
Yong Guan, Hao Peng, Xiaozhi Wang +2
Future event prediction (FEP) is a long-standing and crucial task in the world, as understanding the evolution of events enables early risk identification, informed decision-making…
MAVEN-Fact: A Large-scale Event Factuality Detection Dataset
Chunyang Li, Hao Peng, Xiaozhi Wang +4
Event Factuality Detection (EFD) task determines the factuality of textual events, i.e., classifying whether an event is a fact, possibility, or impossibility, which is essential f…
R-Eval: A Unified Toolkit for Evaluating Domain Knowledge of Retrieval Augmented Large Language Models
Shangqing Tu, Yuanchun Wang, Jifan Yu +6
Large language models have achieved remarkable success on general NLP tasks, but they may fall short for domain-specific problems. Recently, various Retrieval-Augmented Large Langu…
Towards Understanding Safety Alignment: A Mechanistic Perspective from Safety Neurons
Jianhui Chen, Xiaozhi Wang, Zijun Yao +3
Large language models (LLMs) excel in various capabilities but pose safety risks such as generating harmful content and misinformation, even after safety alignment. In this paper,…
TacoERE: Cluster-aware Compression for Event Relation Extraction
Yong Guan, Xiaozhi Wang, Lei Hou +4
Event relation extraction (ERE) is a critical and fundamental challenge for natural language processing. Existing work mainly focuses on directly modeling the entire document, whic…
Event GDR: Event-Centric Generative Document Retrieval
Yong Guan, Dingxiao Liu, Jinchen Ma +4
Generative document retrieval, an emerging paradigm in information retrieval, learns to build connections between documents and identifiers within a single model, garnering signifi…
ADELIE: Aligning Large Language Models on Information Extraction
Yunjia Qi, Hao Peng, Xiaozhi Wang +3
Large language models (LLMs) usually fall short on information extraction (IE) tasks and struggle to follow the complex instructions of IE tasks. This primarily arises from LLMs no…