Summary of Enhancing Trust in Llms: Algorithms For Comparing and Interpreting Llms, by Nik Bear Brown
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMsby Nik Bear BrownFirst submitted to…
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMsby Nik Bear BrownFirst submitted to…
Focus on the Core: Efficient Attention via Pruned Token Compression for Document Classificationby Jungmin Yun,…
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Functionby Keyon…
Formality Style Transfer in Persianby Parastoo Falakaflaki, Mehrnoush ShamsfardFirst submitted to arxiv on: 2 Jun…
Guiding and Diversifying LLM-Based Story Generation via Answer Set Programmingby Phoebe J. Wang, Max KreminskiFirst…
UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulationby Hanzhang Zhou, Zijian…
Robust Planning with LLM-Modulo Framework: Case Study in Travel Planningby Atharva Gundawar, Mudit Verma, Lin…
Quo Vadis ChatGPT? From Large Language Models to Large Knowledge Modelsby Venkat Venkatasubramanian, Arijit ChakrabortyFirst…
Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generationby Anjanava Biswas, Wrick TalukdarFirst…
Unlocking Futures: A Natural Language Driven Career Prediction System for Computer Science and Software Engineering…