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ToFu achieves superior token efficiency and cost-effectiveness in agentic coding, all while empowering researchers with a transparent, modifiable framework.
SPRI achieves a remarkable 3.39 BLEU point improvement over the best existing MoE upcycling method, demonstrating that pretrained weight structures can be effectively leveraged for better expert diversity.
By explicitly structuring and managing retrieval state, EfficientGraph-RAG achieves state-of-the-art RAG performance while slashing large-model token usage by over 3x.
Stop LLMs from drifting to English when reasoning in other languages: language-adaptive RL can guide them to stay consistent without sacrificing performance.
Supervised fine-tuning can be dramatically improved by explicitly encouraging exploration of low-confidence data and suppressing high-confidence errors, leading to sustained gains in mathematical reasoning even after extensive RLVR training.
