LoResMT@ACL 2024: Learning-From-Mistakes Prompting for Indigenous Language Translation – A feedback-driven approach to enhance low-resource translation.
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Updated
Dec 6, 2024 - Python
LoResMT@ACL 2024: Learning-From-Mistakes Prompting for Indigenous Language Translation – A feedback-driven approach to enhance low-resource translation.
Bitext mining for low-resourced Middle Eastern Languages - IWSLT2025
[ACL 2021] OntoED: Low-resource Event Detection with Ontology Embedding
Original PyTorch implementation for TASLP 2022 Paper "SPEC: Summary Preference Decomposition for Low-Resource Abstractive Summarization."
Source code for paper "PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration", Findings of IJCNLP-AACL 2023
Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference
Visualizing heap usage on a graph for embedded systems
Original PyTorch implementation for ICCV 2023 Paper "SINC: Self-Supervised In-Context Learning for Vision-Language Tasks."
Official Codebase for "MunTTS: A Text-to-Speech System for Mundari" (published in ComputEL-7)
[EMNLP 2022 Findings] Towards Realistic Low-resource Relation Extraction: A Benchmark with Empirical Baseline Study
EMNLP-2020: Cross-lingual Spoken Language Understanding with Regularized Representation Alignment
This repository is an open-source colleciton of various low-resource machine translation experiments.
Exploring ways to reduce Neural Machine Translation Memory and Computation through binarized networks
Original PyTorch implementation for AAAI 2021 Paper "Meta-Transfer Learning for Low-Resrouce Abstractive Summarization."
In search of effective and efficient Pipeline for Distillating Knowledge in Convolutional Neural Networks
Exploring Self-Supervised Learning for Low-Resource Medical Image Analysis, ICIP 2023
[SIGIR 2023] Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction
Official code for "Too Brittle To Touch: Comparing the Stability of Quantization and Distillation Towards Developing Lightweight Low-Resource MT Models" to appear in WMT 2022.
Code of ICKG2020 best student paper: A Robust and Domain-Adaptive Approach for Low-Resource Named Entity Recognition
Zero-shot Cross-lingual Task-Oriented Dialogue Systems (EMNLP 2019)
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