Papers by Sruthi Gorantla
Split-Merge: Scalable and Memory-Efficient Merging of Expert LLMs (2025.emnlp-main)
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| Challenge: | a zero-shot merging framework for large language models consolidates specialized domain experts into a single model without any further training. |
| Approach: | They propose a zero-shot merging framework that consolidates specialized domain experts into a single model without further training. |
| Outcome: | Experiments on code generation, mathematical reasoning, medical question answering, and instruction-following benchmarks confirm the versatility and effectiveness of the proposed framework. |
CASCADE: Contextual Sarcasm Detection in Online Discussion Forums (C18-1)
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| Challenge: | Existing studies on sarcasm detection focus on lexical, syntactic and semantic cues, but sarcasm can be expressed implicitly without such cue. |
| Approach: | They propose a ContextuAl SarCasm DEtector which extracts contextual information from the discourse of a discussion thread. |
| Outcome: | The proposed model improves on a large Reddit corpus. |