3 papers
cs.AI2026
The Path of Least Resistance: Guiding LLM Reasoning Trajectories with Prefix Consensus
Ishan Jindal, Sai Prashanth Akuthota, Jayant Taneja +1
Large language models achieve strong reasoning performance, but inference strategies such as Self-Consistency (SC) are computationally expensive, as they fully expand all reasoning…
cs.LG2025
Pre-Hoc Predictions in AutoML: Leveraging LLMs to Enhance Model Selection and Benchmarking for Tabular datasets
Yannis Belkhiter, Seshu Tirupathi, Giulio Zizzo +2
The field of AutoML has made remarkable progress in post-hoc model selection, with libraries capable of automatically identifying the most performing models for a given dataset. Ne…
cs.CL2024
Balancing Continuous Pre-Training and Instruction Fine-Tuning: Optimizing Instruction-Following in LLMs
Ishan Jindal, Chandana Badrinath, Pranjal Bharti +2
Large Language Models (LLMs) for public use require continuous pre-training to remain up-to-date with the latest data. The models also need to be fine-tuned with specific instructi…