Joint optimization for greedy longest-match tokenization (JOLT) develops a subword vocabulary learned to optimize greedy left-to-right longest-match decoding for WordPiece
Read the original at arxiv.org→arXiv:2607.23362v1 Announce Type: new Abstract: Recent work has shown that subword vocabularies can be trained to optimize compression for a specific inference rule rather than relying on greedy heuristics such as...
Original headline: "Joint Optimization for Greedy Longest-match Tokenization"
Coverage timeline
- Jul 28, 04:00 UTC arXiv cs.CL lead source Joint Optimization for Greedy Longest-match Tokenization