36 citations · 58 across the 19 of their papers we have counts for
17 papers · 1 filter
DiSRouter: Distributed Self-Routing for LLM Selections
Hang Zheng, Hongshen Xu, Yongkai Lin +3
The proliferation of Large Language Models (LLMs) has created a diverse ecosystem of models with highly varying performance and costs, necessitating effective query routing to bala…
Delusions of Large Language Models
Hongshen Xu, Zixv yang, Zichen Zhu +7
Large Language Models often generate factually incorrect but plausible outputs, known as hallucinations. We identify a more insidious phenomenon, LLM delusion, defined as high beli…
Alignment for Efficient Tool Calling of Large Language Models
Hongshen Xu, Zihan Wang, Zichen Zhu +4
Recent advancements in tool learning have enabled large language models (LLMs) to integrate external tools, enhancing their task performance by expanding their knowledge boundaries…
Enhancing LLM Reliability via Explicit Knowledge Boundary Modeling
Hang Zheng, Hongshen Xu, Yuncong Liu +3
Large language models (LLMs) are prone to hallucination stemming from misaligned self-awareness, particularly when processing queries exceeding their knowledge boundaries. While ex…
Reducing Tool Hallucination via Reliability Alignment
Hongshen Xu, Zichen Zhu, Lei Pan +6
Large Language Models (LLMs) have expanded their capabilities beyond language generation to interact with external tools, enabling automation and real-world applications. However,…
Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity
Da Ma, Lu Chen, Situo Zhang +8
The rapid expansion of context window sizes in Large Language Models~(LLMs) has enabled them to tackle increasingly complex tasks involving lengthy documents. However, this progres…
Sparsity-Accelerated Training for Large Language Models
Da Ma, Lu Chen, Pengyu Wang +6
Large language models (LLMs) have demonstrated proficiency across various natural language processing (NLP) tasks but often require additional training, such as continual pre-train…
CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editions
Hanchong Zhang, Ruisheng Cao, Hongshen Xu +2
Recently, Large Language Models (LLMs) have been demonstrated to possess impressive capabilities in a variety of domains and tasks. We investigate the issue of prompt design in the…
Multilingual Brain Surgeon: Large Language Models Can be Compressed Leaving No Language Behind
Hongchuan Zeng, Hongshen Xu, Lu Chen +1
Large Language Models (LLMs) have ushered in a new era in Natural Language Processing, but their massive size demands effective compression techniques for practicality. Although nu…
Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback
Hongshen Xu, Zichen Zhu, Situo Zhang +4
Large Language Models (LLMs) often generate erroneous outputs, known as hallucinations, due to their limitations in discerning questions beyond their knowledge scope. While address…
Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding
Hongshen Xu, Lu Chen, Zihan Zhao +4
The growing prevalence of visually rich documents, such as webpages and scanned/digital-born documents (images, PDFs, etc.), has led to increased interest in automatic document und…
A BiRGAT Model for Multi-intent Spoken Language Understanding with Hierarchical Semantic Frames
Hongshen Xu, Ruisheng Cao, Su Zhu +4
Previous work on spoken language understanding (SLU) mainly focuses on single-intent settings, where each input utterance merely contains one user intent. This configuration signif…
Developing ChemDFM as a large language foundation model for chemistry
Zihan Zhao, Da Ma, Lu Chen +11
Artificial intelligence (AI) has played an increasingly important role in chemical research. However, most models currently used in chemistry are specialist models that require tra…
ASTormer: An AST Structure-aware Transformer Decoder for Text-to-SQL
Ruisheng Cao, Hanchong Zhang, Hongshen Xu +4
Text-to-SQL aims to generate an executable SQL program given the user utterance and the corresponding database schema. To ensure the well-formedness of output SQLs, one prominent a…
ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought
Hanchong Zhang, Ruisheng Cao, Lu Chen +2
Recently Large Language Models (LLMs) have been proven to have strong abilities in various domains and tasks. We study the problem of prompt designing in the text-to-SQL task and a…
Large Language Models Are Semi-Parametric Reinforcement Learning Agents
Danyang Zhang, Lu Chen, Situo Zhang +3
Inspired by the insights in cognitive science with respect to human memory and reasoning mechanism, a novel evolvable LLM-based (Large Language Model) agent framework is proposed a…
TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages
Zihan Zhao, Lu Chen, Ruisheng Cao +3
Recently, the structural reading comprehension (SRC) task on web pages has attracted increasing research interests. Although previous SRC work has leveraged extra information such…