55 citations · 86 across the 11 of their papers we have counts for
4 papers · 1 filter
Composing Policy Gradients and Prompt Optimization for Language Model Programs
Noah Ziems, Dilara Soylu, Lakshya A Agrawal +10
Group Relative Policy Optimization (GRPO) has proven to be an effective tool for post-training language models (LMs). However, AI systems are increasingly expressed as modular prog…
GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
Lakshya A Agrawal, Shangyin Tan, Dilara Soylu +14
Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often requir…
ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring
Kaili Huang, Thejas Venkatesh, Uma Dingankar +9
We study serving retrieval models, specifically late interaction models like ColBERT, to many concurrent users at once and under a small budget, in which the index may not fit in m…
WARP: An Efficient Engine for Multi-Vector Retrieval
Jan Luca Scheerer, Matei Zaharia, Christopher Potts +2
Multi-vector retrieval methods such as ColBERT and its recent variant, the ConteXtualized Token Retriever (XTR), offer high accuracy but face efficiency challenges at scale. To add…