BODHI: Do LLMs Branch Out and Discover Heterogeneous Inferences?

arXiv:2608.02867 · cs.CL, cs.AI · Submitted 2026-08-03 · Read on arXiv

Soumadeep Saha, Krish Sharma, Akshay Chaturvedi, Nicholas Asher

cs.CL, cs.AI

Submitted: 2026-08-03

Comments: 16 pages, 10 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Trace — 34× in this paper · explained in 2 episodes
• Verifier — 14× in this paper · explained in 2 episodes
• Entropy Collapse — 12× in this paper · explained in 2 episodes
• Reinforcement Learning — 11× in this paper · explained in 4 episodes
• Distillation — 10× in this paper · explained in 2 episodes
• Reasoning Traces — 8× in this paper · explained in 3 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• GRPO — 3× in this paper · explained in 6 episodes
• Sample Efficiency — 3× in this paper · explained in 4 episodes
• Semantic Similarity — 3× in this paper · explained in 2 episodes
• Verifiable Rewards — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Annotator Agreement — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 2× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Curriculum Reinforcement Learning Can Incentivize Reasoning Capacity in LLMs Beyond the Base Model
• DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
• TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling
• Understanding R1-Zero-Like Training: A Critical Perspective
• gpt-oss-120b & gpt-oss-20b Model Card
• A Configurable Library for Generating and Manipulating Maze Datasets
• Local Coherence or Global Validity? Investigating RLVR Traces in Math Domains
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Gemma 3 Technical Report
• Understanding Diversity Collapse in RLVR via the Lens of Overtraining
• First Return, Entropy-Eliciting Explore
• Qwen3 Technical Report
• TreeRPO: Tree Relative Policy Optimization

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