4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.AI2026
KARL: Knowledge Agents via Reinforcement Learning
Jonathan D. Chang, Andrew Drozdov, Shubham Toshniwal +23
We present a system for training enterprise search agents via reinforcement learning that achieves state-of-the-art performance across a diverse suite of hard-to-verify agentic sea…
cs.CL2024★ 4 cited
MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining
Jacob Portes, Alex Trott, Sam Havens +6
Although BERT-style encoder models are heavily used in NLP research, many researchers do not pretrain their own BERTs from scratch due to the high cost of training. In the past hal…
cs.LG2023★ 1 cited
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms
Aditi Jha, Sam Havens, Jeremy Dohmann +2
Large Language Models are traditionally finetuned on large instruction datasets. However recent studies suggest that small, high-quality datasets can suffice for general purpose in…