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20202026
most citedA Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

2.1k citations · 2.1k across the 20 of their papers we have counts for

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Showing 2023Show all

11 papers · 1 filter

cs.CL2023

Mixed Distillation Helps Smaller Language Model Better Reasoning

Chenglin Li, Qianglong Chen, Liangyue Li +4

While large language models (LLMs) have demonstrated exceptional performance in recent natural language processing (NLP) tasks, their deployment poses substantial challenges due to…

cs.CL2023★ 2 cited

Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System

Haotian Wang, Xiyuan Du, Weijiang Yu +5

Multi-agent debate system (MAD) imitating the process of human discussion in pursuit of truth, aims to align the correct cognition of different agents for the optimal solution. It…

cs.CL2023★ 2 cited

TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models

Zheng Chu, Jingchang Chen, Qianglong Chen +4

Grasping the concept of time is a fundamental facet of human cognition, indispensable for truly comprehending the intricacies of the world. Previous studies typically focus on spec…

cs.CL2023★ 8 cited

Trends in Integration of Knowledge and Large Language Models: A Survey and Taxonomy of Methods, Benchmarks, and Applications

Zhangyin Feng, Weitao Ma, Weijiang Yu +7

Large language models (LLMs) exhibit superior performance on various natural language tasks, but they are susceptible to issues stemming from outdated data and domain-specific limi…

cs.CL2023★ 2.1k cited

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Lei Huang, Weijiang Yu, Weitao Ma +8

The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Never…

cs.CL2023

Large Language Models Are Also Good Prototypical Commonsense Reasoners

Chenin Li, Qianglong Chen, Yin Zhang +2

Commonsense reasoning is a pivotal skill for large language models, yet it presents persistent challenges in specific tasks requiring this competence. Traditional fine-tuning appro…

cs.CL2023★ 26 cited

Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future

Zheng Chu, Jingchang Chen, Qianglong Chen +7

Reasoning, a fundamental cognitive process integral to human intelligence, has garnered substantial interest within artificial intelligence. Notably, recent studies have revealed t…

cs.CL2023

WYWEB: A NLP Evaluation Benchmark For Classical Chinese

Bo Zhou, Qianglong Chen, Tianyu Wang +2

To fully evaluate the overall performance of different NLP models in a given domain, many evaluation benchmarks are proposed, such as GLUE, SuperGLUE and CLUE. The fi eld of natura…

cs.CL2023★ 2 cited

Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering

Qianglong Chen, Guohai Xu, Ming Yan +4

Existing knowledge-enhanced methods have achieved remarkable results in certain QA tasks via obtaining diverse knowledge from different knowledge bases. However, limited by the pro…

cs.CL2023

AMTSS: An Adaptive Multi-Teacher Single-Student Knowledge Distillation Framework For Multilingual Language Inference

Qianglong Chen, Feng Ji, Feng-Lin Li +4

Knowledge distillation is of key importance to launching multilingual pre-trained language models for real applications. To support cost-effective language inference in multilingua…

cs.LG2023

Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning

Wenjin Wang, Yunqing Hu, Qianglong Chen +1

Parameter regularization or allocation methods are effective in overcoming catastrophic forgetting in lifelong learning. However, they solve all tasks in a sequence uniformly and i…