Papers by Kenji Fukumizu
Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions (D18-1)
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| Challenge: | Empirically, PHSIC is learned thousands of times faster than an RNN-based PMI while outperforming PMI in accuracy. |
| Approach: | They propose a new kernel-based co-occurrence measure that can be applied to sparse linguistic expressions with a very short learning time. |
| Outcome: | The proposed measure can be applied to sparse linguistic expressions with a very short learning time, and is called the pointwise HSIC. |
Look Before You Leap: A Lookahead Reasoning Quality Gate for Speculative Decoding (2026.eacl-long)
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| Challenge: | Unlike token-level likelihood search, which is myopic and often rewards verbosity, our approach works at an intermediate granularity. |
| Approach: | They propose a lookahead quality gate for speculative decoding that accepts the longest reliable prefix of each k-token lookaheaded draft. |
| Outcome: | The proposed method improves accuracy over baselines while achieving 2.6-7.9 faster generation on math and science benchmarks. |