A multi-agent framework reconstructs the evolutionary graph of post-training LLM datasets, revealing domain patterns like vertical refinement in math data and systemic issues like redundancy and benchmark contamination, then applies it to create a more diverse lineage-aware dataset.
Reasoning with omnithought: A large cot dataset with verbosity and cognitive difficulty annotations
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TrOPD stabilizes on-policy distillation for LLMs with trust-region learning, outlier estimation, and off-policy guidance, outperforming prior OPD methods on reasoning and code benchmarks.
OmniThoughtVis curates 1.8M multimodal CoT samples via teacher distillation, difficulty annotation, and tag-based sampling, yielding consistent gains on nine reasoning benchmarks and allowing 4B models to match or beat undistilled 8B baselines.
NebulaExp reports an empirical post-training pipeline on Qwen3-8B that raises instruct scores from 55.01 to 61.85 and reasoning scores from 73.88 to 75.17 via curated data, SFT, GRPO RL, and OPD/MOPD distillation.
citing papers explorer
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Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs
A multi-agent framework reconstructs the evolutionary graph of post-training LLM datasets, revealing domain patterns like vertical refinement in math data and systemic issues like redundancy and benchmark contamination, then applies it to create a more diverse lineage-aware dataset.
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Trust Region On-Policy Distillation
TrOPD stabilizes on-policy distillation for LLMs with trust-region learning, outlier estimation, and off-policy guidance, outperforming prior OPD methods on reasoning and code benchmarks.
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OmniThoughtVis: A Scalable Distillation Pipeline for Deployable Multimodal Reasoning Models
OmniThoughtVis curates 1.8M multimodal CoT samples via teacher distillation, difficulty annotation, and tag-based sampling, yielding consistent gains on nine reasoning benchmarks and allowing 4B models to match or beat undistilled 8B baselines.
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NebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research
NebulaExp reports an empirical post-training pipeline on Qwen3-8B that raises instruct scores from 55.01 to 61.85 and reasoning scores from 73.88 to 75.17 via curated data, SFT, GRPO RL, and OPD/MOPD distillation.