From the 2 of 5 linked papers with an AI index.
5 papers
Weak-to-Strong On-Policy Distillation
Fangxu Yu, Zinan Lin, Xiaodong Liu +4
The paper proposes Weak-to-Strong On-Policy Distillation (W2S-OPD), a method that improves a large language model by distilling knowledge from multiple weaker models using a constr…
GFlowRL: Scaling Distribution-Matching RL to Large Language Models
Xiaodong Liu, Michael Xu, Jack W. Stokes +3
The paper introduces GFlowRL, a simplified GFlowNet‑style reinforcement learning method that removes the learned partition function and uses an in‑batch Monte Carlo estimate, enabl…
Mechanisms of Symbol Processing for In-Context Learning in Transformer Networks
Paul Smolensky, Roland Fernandez, Zhenghao Herbert Zhou +3
Large Language Models (LLMs) have demonstrated impressive abilities in symbol processing through in-context learning (ICL). This success flies in the face of decades of critiques a…
TRA: Better Length Generalisation with Threshold Relative Attention
Mattia Opper, Roland Fernandez, Paul Smolensky +1
Transformers struggle with length generalisation, displaying poor performance even on basic tasks. We test whether these limitations can be explained through two key failures of th…
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
Paul Soulos, Henry Conklin, Mattia Opper +3
Neural networks continue to struggle with compositional generalization, and this issue is exacerbated by a lack of massive pre-training. One successful approach for developing neur…