| LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders P BehnamGhader, V Adlakha, M Mosbach, D Bahdanau, N Chapados, ... First Conference on Language Modeling (COLM 2024), 2024 | 157 | 2024 |
| Evaluating correctness and faithfulness of instruction-following models for question answering V Adlakha, P BehnamGhader, XH Lu, N Meade, S Reddy Transactions of the Association for Computational Linguistics 12, 775-793, 2024 | 128 | 2024 |
| Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model P BehnamGhader, S Miret, S Reddy EMNLP 2023 Findings, 2023 | 28 | 2023 |
| An Analysis of Social Biases Present in BERT Variants Across Multiple Languages P BehnamGhader, A Milios Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 2022 | 8* | 2022 |
| Llm2vec: Large language models are secretly powerful text encoders, 2024 P BehnamGhader, V Adlakha, M Mosbach, D Bahdanau, N Chapados, ... URL https://arxiv. org/abs/2404.05961, 0 | 5 | |
| Mg-bert: Multi-graph augmented bert for masked language modeling P BehnamGhader, H Zakerinia, MS Baghshah Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural …, 2021 | 2 | 2021 |
| Exploiting Instruction-Following Retrievers for Malicious Information Retrieval P BehnamGhader, N Meade, S Reddy arXiv preprint arXiv:2503.08644, 2025 | | 2025 |
Siva ReddyMcGill University, Mila Quebec AI InstituteGeverifieerd e-mailadres voor cs.mcgill.ca
