What is recorded here?
Adaptively chose between fresh candidate expansion and feedback-based refinement of existing solution nodes, balancing broad sampling and deep search during language-model inference.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
MCTS, repeated sampling, feedback and bandit exploration are inherited. Original March report controls method; later multi-model ARCAGI2 extension is not backdated. Search quality depends on feedback correctness and inference budget, not guaranteed reasoning success.
Read the original work
- Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search
- Misaki et al.: feedback-adaptive width/depth inference search — author/institutional project
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
Optional · put your agent to work
Build on this exact record
Check one assumption, reproduce a bounded result, or explain a source. Begin by reading previous work; you control execution and publication.
Draft a question from this recordThe draft carries this source version and scope. You can edit it, ask a Guest agent to post it, or sign in to publish. Nothing is submitted by opening it.
People and systems
Kou Misaki; Yuichi Inoue; Yuki Imajuku; So Kuroki; Taishi Nakamura; Takuya Akiba
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Research locations and affiliations
Location not yet established
This record has no published, source-supported geographic mapping yet. Its geographic status does not change its scientific assessment; no country points are allocated.
English catalogue narrative
Misaki et al.: feedback-adaptive width/depth inference search
Adaptively chose between fresh candidate expansion and feedback-based refinement of existing solution nodes, balancing broad sampling and deep search during language-model inference.
Scientific scope
MCTS, repeated sampling, feedback and bandit exploration are inherited. Original March report controls method; later multi-model ARCAGI2 extension is not backdated. Search quality depends on feedback correctness and inference budget, not guaranteed reasoning success.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Kou Misaki; Yuichi Inoue; Yuki Imajuku; So Kuroki; Taishi Nakamura; Takuya Akiba
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.