CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Paper • 2601.18026 • Published
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Open language models for South-East Asia
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jjzha
authored 4
papers 7 days ago
UniSkill: A Dataset for Matching University Curricula to Professional Competencies
Paper • 2603.03134 • Published
WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain
Paper • 2604.13055 • Published
CroCo: Cross-Lingual Contrastive Preference Tuning on Self-Generations
Paper • 2605.26293 • Published • 6
jjzha
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paper to Daily Papers 8 days ago
taicheng
authored 2
papers 17 days ago
taicheng
submitted a
paper to Daily Papers 23 days ago
jojo-ai-mst
posted an update about 1 month ago
Post
173
🇲🇲 Releasing the Myanmar Tuberculosis Instruction Dataset — a Myanmar–English parallel corpus for medical NLP in one of the lowest-resourced language settings in Southeast Asia.
Most TB datasets are either structured clinical data or English-only research corpora. This one fills a different gap: instructional, guideline-based content in Burmese, formatted for instruction tuning and medical QA.
### What's inside
- 2,043 instruction–response pairs
- Myanmar–English parallel
- 7 TB domains: treatment, diagnostics, drug management, MDR-TB, infection control, patient education, healthcare worker training
- Sourced from WHO guidelines, Myanmar NTP protocols, and standard medical references
- MIT licensed
Useful for
- Fine-tuning Myanmar-language medical LLMs
- TB question answering
- Translation evaluation in a medical domain
- General low-resource medical NLP
👉 jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions
Built by Min Si Thu and Khin Myat Noe. Feedback welcome — especially from anyone working on SEA medical AI or Burmese NLP.
#MedicalAI #LowResourceNLP #Myanmar #Burmese #Tuberculosis #InstructionTuning
Most TB datasets are either structured clinical data or English-only research corpora. This one fills a different gap: instructional, guideline-based content in Burmese, formatted for instruction tuning and medical QA.
### What's inside
- 2,043 instruction–response pairs
- Myanmar–English parallel
- 7 TB domains: treatment, diagnostics, drug management, MDR-TB, infection control, patient education, healthcare worker training
- Sourced from WHO guidelines, Myanmar NTP protocols, and standard medical references
- MIT licensed
Useful for
- Fine-tuning Myanmar-language medical LLMs
- TB question answering
- Translation evaluation in a medical domain
- General low-resource medical NLP
from datasets import load_dataset
ds = load_dataset("jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions")👉 jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions
Built by Min Si Thu and Khin Myat Noe. Feedback welcome — especially from anyone working on SEA medical AI or Burmese NLP.
#MedicalAI #LowResourceNLP #Myanmar #Burmese #Tuberculosis #InstructionTuning
muhammadravi251001
authored 3
papers about 2 months ago
Global PIQA: Evaluating Physical Commonsense Reasoning Across 100+ Languages and Cultures
Paper • 2510.24081 • Published • 24
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Paper • 2601.18026 • Published
Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
Paper • 2604.11490 • Published • 16
patrickamadeus
authored 5
papers 2 months ago
Seeing Culture: A Benchmark for Visual Reasoning and Grounding
Paper • 2509.16517 • Published • 3
Vision Language Models are Confused Tourists
Paper • 2511.17004 • Published • 1
Can Large Language Models Understand, Reason About, and Generate Code-Switched Text?
Paper • 2601.07153 • Published
M4-RAG: A Massive-Scale Multilingual Multi-Cultural Multimodal RAG
Paper • 2512.05959 • Published
LinguDistill: Recovering Linguistic Ability in Vision- Language Models via Selective Cross-Modal Distillation
Paper • 2604.00829 • Published • 8
patrickamadeus
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paper to Daily Papers 2 months ago
Muennighoff
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huybery
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paper 4 months ago