Publications (16)
LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model
Linmei Hu, Hongyu He, Duokang Wang +3
Personality detection aims to detect one's personality traits underlying in social media posts. One challenge of this task is the scarcity of ground-truth personality traits which…
Laser: Parameter-Efficient LLM Bi-Tuning for Sequential Recommendation with Collaborative Information
Xinyu Zhang, Linmei Hu, Luhao Zhang +3
Sequential recommender systems are essential for discerning user preferences from historical interactions and facilitating targeted recommendations. Recent innovations employing La…
Multimodal Dialog Systems with Dual Knowledge-enhanced Generative Pretrained Language Model
Xiaolin Chen, Xuemeng Song, Liqiang Jing +3
Text response generation for multimodal task-oriented dialog systems, which aims to generate the proper text response given the multimodal context, is an essential yet challenging…
SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation
Zijun Yao, Weijian Qi, Liangming Pan +5
This paper introduces Self-aware Knowledge Retrieval (SeaKR), a novel adaptive RAG model that extracts self-aware uncertainty of LLMs from their internal states. SeaKR activates re…
ActiShade: Activating Overshadowed Knowledge to Guide Multi-Hop Reasoning in Large Language Models
Huipeng Ma, Luan Zhang, Dandan Song +10
In multi-hop reasoning, multi-round retrieval-augmented generation (RAG) methods typically rely on LLM-generated content as the retrieval query. However, these approaches are inher…
ChatLLM Network: More brains, More intelligence
Rui Hao, Linmei Hu, Weijian Qi +3
Dialogue-based language models mark a huge milestone in the field of artificial intelligence, by their impressive ability to interact with users, as well as a series of challenging…
AeSlides: Incentivizing Aesthetic Layout in LLM-Based Slide Generation via Verifiable Rewards
Yiming Pan, Chengwei Hu, Xuancheng Huang +6
Large language models (LLMs) have demonstrated strong potential in agentic tasks, particularly in slide generation. However, slide generation poses a fundamental challenge: the gen…
RefineCoder: Iterative Improving of Large Language Models via Adaptive Critique Refinement for Code Generation
Changzhi Zhou, Xinyu Zhang, Dandan Song +6
Code generation has attracted increasing attention with the rise of Large Language Models (LLMs). Many studies have developed powerful code LLMs by synthesizing code-related instru…
Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences
Rui Hao, Dianbo Liu, Linmei Hu
The merging of human intelligence and artificial intelligence has long been a subject of interest in both science fiction and academia. In this paper, we introduce a novel concept…
Multimodal Matching-aware Co-attention Networks with Mutual Knowledge Distillation for Fake News Detection
Linmei Hu, Ziwang Zhao, Weijian Qi +2
Fake news often involves multimedia information such as text and image to mislead readers, proliferating and expanding its influence. Most existing fake news detection methods appl…
How Proficient Are Large Language Models in Formal Languages? An In-Depth Insight for Knowledge Base Question Answering
Jinxin Liu, Shulin Cao, Jiaxin Shi +5
Knowledge Base Question Answering (KBQA) aims to answer natural language questions based on facts in knowledge bases. A typical approach to KBQA is semantic parsing, which translat…
SCoder: Iterative Self-Distillation for Bootstrapping Small-Scale Data Synthesizers to Empower Code LLMs
Xinyu Zhang, Changzhi Zhou, Linmei Hu +5
Existing code large language models (LLMs) often rely on large-scale instruction data distilled from proprietary LLMs for fine-tuning, which typically incurs high costs. In this pa…
KB-Plugin: A Plug-and-play Framework for Large Language Models to Induce Programs over Low-resourced Knowledge Bases
Jiajie Zhang, Shulin Cao, Linmei Hu +3
Program induction (PI) has become a promising paradigm for using knowledge bases (KBs) to help large language models (LLMs) answer complex knowledge-intensive questions. Nonetheles…
Graph Neural News Recommendation with Long-term and Short-term Interest Modeling
Linmei Hu, Chen Li, Chuan Shi +2
With the information explosion of news articles, personalized news recommendation has become important for users to quickly find news that they are interested in. Existing methods…
A Survey of Knowledge Enhanced Pre-trained Language Models
Linmei Hu, Zeyi Liu, Ziwang Zhao +3
Pre-trained Language Models (PLMs) which are trained on large text corpus via self-supervised learning method, have yielded promising performance on various tasks in Natural Langua…
Relation Structure-Aware Heterogeneous Information Network Embedding
Yuanfu Lu, Chuan Shi, Linmei Hu +1
Heterogeneous information network (HIN) embedding aims to embed multiple types of nodes into a low-dimensional space. Although most existing HIN embedding methods consider heteroge…