Papers by Samar Haider
Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual Robustness (2025.findings-acl)
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Bryan Li, Fiona Luo, Samar Haider, Adwait Agashe, Siyu Li, Runqi Liu, Miranda Muqing Miao, Shriya Ramakrishnan, Yuan Yuan, Chris Callison-Burch
| Challenge: | Existing approaches to retrieval-augmented generated (RAG) can be useful in multilingual settings, but they also introduce biases in the retrieved documents. |
| Approach: | They propose a dataset of territorial disputes paired with retrieved Wikipedia documents in 49 languages to evaluate cross-lingual robustness. |
| Outcome: | The proposed paradigm helps mitigate hallucinations of large language models (LLMs). |
This Land is Your, My Land: Evaluating Geopolitical Bias in Language Models through Territorial Disputes (2024.naacl-long)
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| Challenge: | Pretrained large language models may answer differently in different languages . this contrasts with a multilingual human, who would likely answer consistently . |
| Approach: | They propose a dataset of territorial disputes which includes multiple-choice questions in 49 languages . they propose metrics to quantify bias and consistency in responses across different languages based on their data . |
| Outcome: | The proposed model recalls certain knowledge inconsistently when asked in different languages. |
Urdu Word Embeddings (L18-1)
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| Challenge: | Recent advances in distributional semantics have led to the rise of neural network-based models that use unsupervised learning to represent words as dense, distributed vectors, called 'word embeddings' embedders hold key to improving natural language processing for low-resource languages, since they require significant time and manpower. |
| Approach: | They train a skip-gram model on 140 million Urdu words to create the first large-scale word embeddings for the Urdu language. |
| Outcome: | The proposed models capture high degree of syntactic and semantic similarity between words and are able to generalize well on the Urdu translation task. |