Shizhu He

Neural-Symbolic Collaborative Distillation: Advancing Small Language Models for Complex Reasoning Tasks

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

In this paper, we propose Neural-Symbolic Collaborative Distillation (NesyCD), a novel knowledge distillation method for learning the complex reasoning abilities of Large Language Models (LLMs, e.g., \textgreater 13B). We argue that complex reasoning tasks are …

Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

Distant supervision for relation extraction is an efficient method to scale relation extraction to very large corpora which contains thousands of relations. However, the existing approaches have flaws on selecting valid instances and lack of …

An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge

2017

With the rapid growth of knowledge bases (KBs) on the web, how to take full advantage of them becomes increasingly important. Question answering over knowledge base (KB-QA) is one of the promising approaches to access …

Generating Natural Answers by Incorporating Copying and Retrieving Mechanisms in Sequence-to-Sequence Learning

2017

Generating answer with natural language sentence is very important in real-world question answering systems, which needs to obtain a right answer as well as a coherent natural response.

Large Scaled Relation Extraction With Reinforcement Learning

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Sentence relation extraction aims to extract relational facts from sentences, which is an important task in natural language processing field. Previous models rely on the manually labeled supervised dataset. However, the human annotation is costly …

Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism

2018

The relational facts in sentences are often complicated. Different relational triplets may have overlaps in a sentence. We divided the sentences into three types according to triplet overlap degree, including Normal, EntityPairOverlap and SingleEn-tiyOverlap. Existing …

Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning

2019

Xiangrong Zeng, Shizhu He, Daojian Zeng, Kang Liu, Shengping Liu, Jun Zhao. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). …