277 citations · 353 across the 16 of their papers we have counts for
4 papers · 1 filter
Metropolis-Hastings Dominates Importance Resampling for Policy Composition
Alexey Kurennoy, Ramil Yarullin, Fergal Reid
Post-training a large language model (LLM) often requires exploring trade-offs between multiple rewards, but retraining for each trade-off is expensive. Decoding-time policy compos…
Looped Latent Attention: Cross-Loop KV Compression for Looped Transformers
James O' Neill, Fergal Reid
Looped, weight-tied Transformers reduce parameters by reusing a single block, but decoding still stores a separate K/V cache for every recurrence step. We show that this loop-index…
When RL Suppresses Its Own Vocabulary: Recovering Reasoning Diversity in Puzzle-to-Math Transfer
Mayug Maniparambil, Arjun Karuvally, Terrence Sejnowski +1
Reinforcement learning using verifiable rewards (RLVR) improves LLM reasoning, but the conditions under which it transfers across domains -- and why it does so -- remain under-expl…
Low-Rank Key Value Attention
James O'Neill, Robert Clancy, Mariia Matskevichus +1
The key-value (KV) cache is a primary memory bottleneck in Transformers. We propose Low-Rank Key-Value (LRKV) attention, which reduces KV cache memory by exploiting redundancy acro…