3 citations · 3 across the 8 of their papers we have counts for
10 papers
CalibHyper: Chance-Corrected Relational Hypergraphs for Few-Shot Molecular Property Prediction
Linyu Li, Zhi Jin, Yuanpeng He +7
Molecular property prediction is central to drug development and materials discovery, but experiments are costly and labeled data are scarce. Context-aware methods use auxiliary as…
TreeProbe : A Tibetan Medicine Benchmark for Cultural Bias in LLMs
Jin Zhang, Linyu Li, Weili Jiang +7
Large language models are increasingly viewed as a potential means of mitigating global health inequities, yet their outputs often reflect dominant high-resource medical traditions…
Knowledge before Reasoning: EC-Reason-Bench, a Training-Free Diagnostic Benchmark for LLM Enzyme Classification
Linyu Li, Zhi Jin, Yichi Zhang +6
Enzyme function prediction is a hierarchical, knowledge-intensive form of protein function classification. Existing benchmarks expose an anomaly: general LLMs often get the coarse…
When Modalities Remember: Continual Learning for Multimodal Knowledge Graphs
Linyu Li, Zhi Jin, Yichi Zhang +5
Real-world multimodal knowledge graphs (MMKGs) are dynamic, with new entities, relations, and multimodal knowledge emerging over time. Existing continual knowledge graph reasoning…
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…
RetrieveAll: A Multilingual Named Entity Recognition Framework with Large Language Models
Jin Zhang, Fan Gao, Linyu Li +4
The rise of large language models has led to significant performance breakthroughs in named entity recognition (NER) for high-resource languages, yet there remains substantial room…
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…
TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency
Dan Zhang, Rui Zheng, Luosang Gadeng +1
This paper addresses the task of semantic segmentation in computer vision, aiming to achieve precise pixel-wise classification. We investigate the joint training of models for sema…