Papers by Thomas Gschwind
Classifier-Augmented Generation for Structured Workflow Prediction (2025.emnlp-industry)
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| Challenge: | a new system translates natural language descriptions into executable workflows . configuring stages and their properties is time consuming and requires deep tool knowledge. |
| Approach: | They propose a system that translates natural language descriptions into executable workflows . it uses a Classifier-Augmented Generation approach that combines utterance decomposition with a classifier and stage-specific prompting to produce accurate stage predictions. |
| Outcome: | The proposed system outperforms existing models and reduces token usage by 60%. |
Adapting LLMs for Structured Natural Language API Integration (2024.emnlp-industry)
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Robin Chan, Katsiaryna Mirylenka, Thomas Gschwind, Christoph Miksovic, Paolo Scotton, Enrico Toniato, Abdel Labbi
| Challenge: | API integration is crucial for enterprise systems, but there are challenges in combining APIs based on user intent. |
| Approach: | They propose a framework that leverages large language models to integrate APIs based on natural language input. |
| Outcome: | The proposed framework improves performance over existing methods and RAGs based on open APIs . it can learn structural API constraints implicitly during training and retain structured knowledge . |