Papers by Aditya Parameswaran
Class Name Guided Out-of-Scope Intent Classification (2024.findings-emnlp)
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Chandan Gautam, Sethupathy Parameswaran, Aditya Kane, Yuan Fang, Savitha Ramasamy, Suresh Sundaram, Sunil Sahu, Xiaoli Li
| Challenge: | SCOOS leverages semantic cues embedded in class labels to improve classification accuracy. |
| Approach: | They propose a method to create a compact feature space around class label semantics . they use a shared latent space between ID features and class names to minimize losses . |
| Outcome: | The proposed method outperforms existing methods for out-of-scope intent detection and ID intent classification. |
PROMPTEVALS: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines (2025.naacl-long)
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| Challenge: | Large language models fail to follow instructions or meet developer expectations when running in production . a dataset of 2087 LLM pipeline prompts with 12623 assertion criteria is larger than previous collections . |
| Approach: | They propose a dataset of 2087 LLM pipeline prompts with 12623 assertion criteria . they fine-tuned Mistral and Llama 3 models outperform GPT-4o by 20.93% on average . |
| Outcome: | The proposed dataset outperforms GPT-4o and mistral models in generating assertions and offers reduced latency and improved performance. |