The paper introduces Manta-LM, which approximates the Hamilton-Jacobi-Bellman optimal policy via Flow Matching in a rectified latent control space to enable high-fidelity parallel language generation.
Infinity instruct: Scaling instruction selection and synthesis to enhance language models
7 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
SlimSpec replaces the standard LM-head in draft models with a low-rank version to deliver 4-5x faster speculative decoding while preserving full vocabulary and competitive acceptance rates.
K12-KGraph is a textbook-derived knowledge graph that powers a new benchmark revealing LLMs' poor curriculum cognition and a small training corpus that outperforms general instruction data on educational tasks.
VITA-QinYu is the first expressive end-to-end spoken language model supporting role-playing and singing alongside conversation, trained on 15.8K hours of data and outperforming prior models on expressiveness and conversational benchmarks.
ShareChat is a large-scale dataset of 142,808 conversations from five major chatbot platforms that retains native affordances for cross-platform analyses of completeness, citations, and latency.
EdgeRazor uses structural mixed-precision quantization, layer-adaptive feature distillation, and entropy-aware KL divergence to achieve 1.88-bit LLMs that outperform prior 2-bit and 3-bit baselines with 4-10x lower training budget.
MAR integrates SSMs and sparsification with new ATMN neurons and SBDS distillation to produce efficient LLMs that match dense-model performance at substantially lower inference energy.
citing papers explorer
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Language Generation as Optimal Control: Closed-Loop Diffusion in Latent Control Space
The paper introduces Manta-LM, which approximates the Hamilton-Jacobi-Bellman optimal policy via Flow Matching in a rectified latent control space to enable high-fidelity parallel language generation.
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SlimSpec: Low-Rank Draft LM-Head for Accelerated Speculative Decoding
SlimSpec replaces the standard LM-head in draft models with a low-rank version to deliver 4-5x faster speculative decoding while preserving full vocabulary and competitive acceptance rates.
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K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs
K12-KGraph is a textbook-derived knowledge graph that powers a new benchmark revealing LLMs' poor curriculum cognition and a small training corpus that outperforms general instruction data on educational tasks.
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VITA-QinYu: Expressive Spoken Language Model for Role-Playing and Singing
VITA-QinYu is the first expressive end-to-end spoken language model supporting role-playing and singing alongside conversation, trained on 15.8K hours of data and outperforming prior models on expressiveness and conversational benchmarks.
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ShareChat: A Dataset of Chatbot Conversations in the Wild
ShareChat is a large-scale dataset of 142,808 conversations from five major chatbot platforms that retains native affordances for cross-platform analyses of completeness, citations, and latency.
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EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation
EdgeRazor uses structural mixed-precision quantization, layer-adaptive feature distillation, and entropy-aware KL divergence to achieve 1.88-bit LLMs that outperform prior 2-bit and 3-bit baselines with 4-10x lower training budget.
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MAR: Efficient Large Language Models via Module-aware Architecture Refinement
MAR integrates SSMs and sparsification with new ATMN neurons and SBDS distillation to produce efficient LLMs that match dense-model performance at substantially lower inference energy.