1 citations · 1 across the 9 of their papers we have counts for
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UBTree: Parallel Tree Drafting via Unigram and Bigram Models for Speculative Decoding
Chumeng Liang, Linxuan Wang, Xinyu Peng +6
Speculative decoding accelerates language model inference by verifying multiple draft tokens in a single target-model pass. Recent parallel drafters have achieved breakthrough perf…
Deciding When to Switch: E-Processes for Adaptive Minimax Training for Generative Adversarial Nets
Hyunjoo Kim, Sicheng Wu, Agastya Venkatraman +2
Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecified statistical models. One impo…
Generalized Discrete Diffusion with Self-Correction
Linxuan Wang, Ziyi Wang, Yikun Bai +3
Self-correction is an effective technique for maintaining parallel sampling in discrete diffusion models with minimal performance degradation. Prior work has explored self-correcti…
f-GRPO and Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment
Rajdeep Haldar, Lantao Mei, Guang Lin +2
Recent work shows that preference alignment objectives can be interpreted as divergence estimators between aligned (preferred) & unaligned (less-preferred) distributions, yielding…
Task-tailored Pre-processing: Fair Downstream Supervised Learning
Jinwon Sohn, Guang Lin, Qifan Song
Fairness-aware machine learning has recently attracted various communities to mitigate discrimination against certain societal groups in data-driven tasks. For fair supervised lear…