Papers by Arman Zharmagambetov
To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning (2024.emnlp-demo)
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Da Ju, Song Jiang, Andrew Cohen, Aaron Foss, Sasha Mitts, Arman Zharmagambetov, Brandon Amos, Xian Li, Justine Kao, Maryam Fazel-Zarandi, Yuandong Tian
| Challenge: | a new system that takes natural language requests from users generates and trains optimal travel plans . a user can provide instructions and an agent provides optimal solutions . the system takes 5seconds to reply to the user request with guaranteed itineraries . |
| Approach: | They propose a real-time demo system that takes natural language requests from users . it translates requests to symbolic form and produces optimal travel itineraries with LLM . |
| Outcome: | The proposed system produces optimal travel itineraries with mixed integer linear programming solvers. |
Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large (2021.emnlp-main)
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| Challenge: | Classification problems with thousands or more classes occur in NLP, for example language models or document classification. |
| Approach: | a new algorithm uses a binary tree with sparse hyperplanes and small softmax classifiers at the leaves to predict the top class. |
| Outcome: | The proposed model is faster at inference because the input follows a single path to a leaf and the softmax classifier operates on a small subset of the classes. |