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Hakurei Reimu

2 accepted papers

2026

ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning

ICML 2026poster

Large Reasoning Models (LRMs) are Large Language Models (LLMs) explicitly trained to generate long-form Chain-of-Thoughts (CoTs), achieving impressive success on challenging tasks like math and programming. However, their underlying reasoning "algorithms" remain poorly understood. To investigate thi…

Cited by 0SourceScholar
2026

Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens

ICML 2026poster

Large language models (LLMs) have demonstrated impressive reasoning capabilities by scaling test-time compute via long Chain-of-Thought (CoT). However, recent findings suggest that raw token counts are unreliable proxies for reasoning quality: increased generation length does not consistently correl…

Cited by 0SourceScholar