24 citations · 24 across the 5 of their papers we have counts for
5 papers
Tibetan Language and AI: A Comprehensive Survey of Resources, Methods and Challenges
Cheng Huang, Nyima Tashi, Fan Gao +19
Tibetan, one of the major low-resource languages in Asia, presents unique linguistic and sociocultural characteristics that pose both challenges and opportunities for AI research.…
TIBSTC-CoT: A Multi-Domain Instruction Dataset for Chain-of-Thought Reasoning in Language Models
Fan Gao, Cheng Huang, Nyima Tashi +11
To address the severe data scarcity in Tibetan, a low-resource language spoken by over six million people, we introduce TIBSTC-CoT, the large-scale, multi-domain Tibetan dataset au…
TiSpell: A Semi-Masked Methodology for Tibetan Spelling Correction covering Multi-Level Error with Data Augmentation
Yutong Liu, Feng Xiao, Ziyue Zhang +10
Multi-level Tibetan spelling correction addresses errors at both the character and syllable levels within a unified model. Existing methods focus mainly on single-level correction…
TLUE: A Tibetan Language Understanding Evaluation Benchmark
Fan Gao, Cheng Huang, Nyima Tashi +9
Large language models have made tremendous progress in recent years, but low-resource languages, like Tibetan, remain significantly underrepresented in their evaluation. Despite Ti…
Machine Intelligence-Driven Classification of Cancer Patients-Derived Extracellular Vesicles using Fluorescence Correlation Spectroscopy: Results from a Pilot Study
Abicumaran Uthamacumaran, Mohamed Abdouh, Kinshuk Sengupta +5
Patient-derived extracellular vesicles (EVs) that contains a complex biological cargo is a valuable source of liquid biopsy diagnostics to aid in early detection, cancer screening,…