1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2024
FSM: A Finite State Machine Based Zero-Shot Prompting Paradigm for Multi-Hop Question Answering
Xiaochen Wang, Junqing He, Zhe yang +4
Large Language Models (LLMs) with chain-of-thought (COT) prompting have demonstrated impressive abilities on simple nature language inference tasks. However, they tend to perform p…
cs.CL2024★ 1 cited
PeriodicLoRA: Breaking the Low-Rank Bottleneck in LoRA Optimization
Xiangdi Meng, Damai Dai, Weiyao Luo +7
Supervised fine-tuning is the most common method to adapt large language models (LLMs) to downstream tasks, but full fine-tuning LLMs requires massive computational resources. Rece…
cs.CL2022
Low-resource Neural Machine Translation with Cross-modal Alignment
Zhe Yang, Qingkai Fang, Yang Feng
How to achieve neural machine translation with limited parallel data? Existing techniques often rely on large-scale monolingual corpora, which is impractical for some low-resource…