52 citations · 55 across the 9 of their papers we have counts for
3 papers · 1 filter
Sparse Mixture-of-Experts Reward Models Learn Interpretable and Specialized Experts for Personalized Preference Modeling
Yifan Wang, Jinyi Mu, Mayank Jobanputra +5
Preference modeling plays a central role in reinforcement learning from human feedback (RLHF), enabling large language models (LLMs) to align with human values. However, most exist…
Can LLMs subtract numbers?
Mayank Jobanputra, Nils Philipp Walter, Maitrey Mehta +7
We present a systematic study of subtraction in large language models (LLMs). While prior benchmarks emphasize addition and multiplication, subtraction has received comparatively l…
Born a Transformer -- Always a Transformer? On the Effect of Pretraining on Architectural Abilities
Mayank Jobanputra, Yana Veitsman, Yash Sarrof +4
Transformers have theoretical limitations in modeling certain sequence-to-sequence tasks, yet it remains largely unclear if these limitations play a role in large-scale pretrained…