5 papers
Hierarchical Latent Prediction for Language Models
Chang Shi, Tim Pearce, Manan Tomar +2
While standard Next-Token Prediction (NTP) lays the foundation of language model pre- training, its teacher-forced training paradigm may not be optimal for long-horizon reasoning a…
Next-Latent Prediction Transformers Learn Compact World Models
Jayden Teoh, Manan Tomar, Kwangjun Ahn +7
Transformers replace recurrence with a memory that grows with sequence length and self-attention that enables ad-hoc lookups over past tokens. Consequently, they lack an inherent i…
DM-Codec: Distilling Multimodal Representations for Speech Tokenization
Md Mubtasim Ahasan, Md Fahim, Tasnim Mohiuddin +6
Recent advancements in speech-language models have yielded significant improvements in speech tokenization and synthesis. However, effectively mapping the complex, multidimensional…
The Belief State Transformer
Edward S. Hu, Kwangjun Ahn, Qinghua Liu +9
We introduce the "Belief State Transformer", a next-token predictor that takes both a prefix and suffix as inputs, with a novel objective of predicting both the next token for the…
Reward Centering
Abhishek Naik, Yi Wan, Manan Tomar +1
We show that discounted methods for solving continuing reinforcement learning problems can perform significantly better if they center their rewards by subtracting out the rewards'…