21 citations · 21 across the 3 of their papers we have counts for
3 papers
All for One: LLMs Solve Mental Math at the Last Token With Information Transferred From Other Tokens
Siddarth Mamidanna, Daking Rai, Ziyu Yao +1
Large language models (LLMs) demonstrate proficiency across numerous computational tasks, yet their inner workings remain unclear. In theory, the combination of causal self-attenti…
Fine-tuning for Better Few Shot Prompting: An Empirical Comparison for Short Answer Grading
Joel Walsh, Siddarth Mamidanna, Benjamin Nye +2
Research to improve Automated Short Answer Grading has recently focused on Large Language Models (LLMs) with prompt engineering and no- or few-shot prompting to achieve best result…
Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations
Shiyuan Huang, Siddarth Mamidanna, Shreedhar Jangam +2
Large language models (LLMs) such as ChatGPT have demonstrated superior performance on a variety of natural language processing (NLP) tasks including sentiment analysis, mathematic…