Papers by Mohd Abbas Zaidi
Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs (2025.acl-long)
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Anshumann Anshumann, Mohd Abbas Zaidi, Akhil Kedia, Jinwoo Ahn, Taehwak Kwon, Kangwook Lee, Haejun Lee, Joohyung Lee
| Challenge: | Knowledge distillation is a cost-effective technique to distill knowledge in Large Language Models, if the teacher output logits can be pre-computed and cached. |
| Approach: | They propose an importance-sampling-based method which provides unbiased estimates, preserves the gradient in expectation, and requires storing significantly sparser logits. |
| Outcome: | The proposed method enables faster training of student models with marginal overhead (10%) compared to cross-entropy based training, while maintaining competitive performance compared with full distillation. |
FiE: Building a Global Probability Space by Leveraging Early Fusion in Encoder for Open-Domain Question Answering (2022.emnlp-main)
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| Challenge: | generative models tend to be larger than extractive models due to the need for a decoder, run slower during inference due to auto-regressive decoded beam search, and their generated output suffers from hallucinations. |
| Approach: | They propose to extend transformer encoders with the ability to fuse information from multiple passages to provide cross-sample attention over all tokens across samples. |
| Outcome: | The proposed method outperforms the current state-of-the-art method by 2.5 Exact Match score on the Natural Question dataset while using only 25% of parameters and 35% of the latency during inference. |
Language Model Augmented Monotonic Attention for Simultaneous Translation (2022.naacl-main)
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| Challenge: | Existing adaptive policies for simultaneous neural machine translation use monotonic attention to perform read/write decisions based on the partial source and target sequences. |
| Approach: | They propose a framework to aid monotonic attention with an external language model to improve its decisions. |
| Outcome: | The proposed approach improves on English-German and English-French translation tasks by using a language model. |