18 citations · 20 across the 6 of their papers we have counts for
6 papers
Neuro-symbolic Learning Yielding Logical Constraints
Zenan Li, Yunpeng Huang, Zhaoyu Li +5
Neuro-symbolic systems combine the abilities of neural perception and logical reasoning. However, end-to-end learning of neuro-symbolic systems is still an unsolved challenge. This…
LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation
Hao Gao, Jingyue Wang, Wenyang Fang +4
Autonomous Driving Systems (ADS) require diverse and safety-critical traffic scenarios for effective training and testing, but the existing data generation methods struggle to prov…
Executing Arithmetic: Fine-Tuning Large Language Models as Turing Machines
Junyu Lai, Jiahe Xu, Yao Yang +3
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing and reasoning tasks. However, their performance in the fou…
MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models
Jingwei Xu, Junyu Lai, Yunpeng Huang
The pretrain+fine-tune paradigm is foundational for deploying large language models (LLMs) across various downstream applications. Within this framework, Low-Rank Adaptation (LoRA)…
Securing Reliability: A Brief Overview on Enhancing In-Context Learning for Foundation Models
Yunpeng Huang, Yaonan Gu, Jingwei Xu +3
As foundation models (FMs) continue to shape the landscape of AI, the in-context learning (ICL) paradigm thrives but also encounters issues such as toxicity, hallucination, dispari…
Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey
Yunpeng Huang, Jingwei Xu, Junyu Lai +9
Transformer-based Large Language Models (LLMs) have been applied in diverse areas such as knowledge bases, human interfaces, and dynamic agents, and marking a stride towards achiev…