Gacha Decoding asks a language model to identify decision axes that define meaningfully different responses.
External randomness helps stronger language models produce more diverse responses
Gacha Decoding uses instruction following and a random-number generator to explore distinct ideas before producing a final response.
Top University
Scott Geng · Yufei Zhang · Joseph Lee · Jerry Li · Marjan Ghazvininejad · Pang Wei Koh
University of Washington · Meta Superintelligence Labs
Research Digest··3 min read
Geng et al.
Why this paper
From University of Washington and Meta Superintelligence Labs
In one line
Treating diversity as an instruction-following problem with external randomness yields more diverse language model outputs that scale with model capability.
What we could check
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