Papers by Harsh Singh
IrEne-viz: Visualizing Energy Consumption of Transformer Models (2021.emnlp-demo)
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Yash Kumar Lal, Reetu Singh, Harsh Trivedi, Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian
| Challenge: | IrEne is an energy prediction system that accurately predicts inference energy consumption of transformer-based NLP models. |
| Approach: | They present an online platform for visualizing and exploring energy consumption of transformer-based NLP models. |
| Outcome: | The proposed system predicts energy consumption of transformer-based models and their components. |
Self-Improvement in Multimodal Large Language Models: A Survey (2025.findings-emnlp)
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| Challenge: | Using data and data, self-improvement for Large Language Models has improved model capabilities without significantly increasing costs. |
| Approach: | This survey provides a comprehensive overview of self-improvement for Large Language Models . it includes commonly used evaluations and downstream applications . |
| Outcome: | The authors provide a comprehensive overview of self-improvement in Multimodal LLMs. |
Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networks (2021.eacl-main)
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| Challenge: | Existing knowledge graphs are widely used for (complex) conversational question answering . LASAGNE improves the F1-score on eight out of ten question types . |
| Approach: | They propose a multi-task neural semantic parsing approach for (complex) conversational question answering over a knowledge graph using a transformer model and a Graph Attention Networks model. |
| Outcome: | The proposed approach outperforms baselines on eight out of ten question types on a standard dataset for complex sequential question answering. |