Tree of Problems: Improving structured problem solving with
  compositionality
Large Language Models (LLMs) have demonstrated remarkable performance across
multiple tasks through in-context learning. For complex reasoning tasks that
require step-by-step thinking, Chain-of-Thought (CoT) prompting has given
impressive results, especially when combined with self-consistency.
Nonetheless, some tasks remain particularly difficult for LLMs to solve. Tree
of Thoughts (ToT) and Graph of Thoughts (GoT) emerged as alternatives, dividing
the complex problem into paths of subproblems. In this paper, we propose Tree
of Problems (ToP), a simpler version of ToT, which we hypothesise can work
better for complex tasks that can be divided into identical subtasks. Our
empirical results show that our approach outperforms ToT and GoT, and in
addition performs better than CoT on complex reasoning tasks. All code for this
paper is publicly available here:
https://github.com/ArmelRandy/tree-of-problems.
670e05ef1cc9c1fdf0a093ff
Armel Zebaze
670e05ef1cc9c1fdf0a09400
Benoît Sagot
admin_assigned
2024-10-15T16:32:56.867Z
602ba2a739515f8d31237967
/avatars/ef534712ca682bf74ec7eef17d3d1b5f.svg
Benoît Sagot
user
sagot
670e05ef1cc9c1fdf0a09401
Rachel Bawden
admin_assigned
2024-10-15T16:33:02.609Z
613a0c85e63aa832a98cecc4
https://cdn-avatars.huggingface.co/v1/production/uploads/1653912785529-613a0c85e63aa832a98cecc4.png
Rachel Bawden
user
rbawden
Tree of Problems: Improving structured problem solving with
  compositionality
Large Language Models (LLMs) have demonstrated remarkable performance across
multiple tasks through in-context learning. For complex reasoning tasks that
require step-by-step thinking, Chain-of-Thought (CoT) prompting has given
impressive results, especially when combined with self-consistency.
Nonetheless, some tasks remain particularly difficult for LLMs to solve. Tree
of Thoughts (ToT) and Graph of Thoughts (GoT) emerged as alternatives, dividing
the complex problem into paths of subproblems. In this paper, we propose Tree
of Problems (ToP), a simpler version of ToT, which we hypothesise can work
better for complex tasks that can be divided into identical subtasks. Our
empirical results show that our approach outperforms ToT and GoT, and in
addition performs better than CoT on complex reasoning tasks. All code for this
paper is publicly available here:
https://github.com/ArmelRandy/tree-of-problems.
A new method, Tree of Problems, improves upon Chain-of-Thought, Tree of Thoughts, and Graph of Thoughts for complex reasoning tasks by simplifying the division of identical subtasks.
Chain-of-Thought Tree of Thoughts Graph of Thoughts Tree of Problems complex reasoning tasks identical subtasks