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Posts by Collection
portfolio
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publications
TARE: Timescale-Aware Row-wise Energy Redistribution for Muon Optimizers
Published in Under review, 2026
Under review. A Muon-family optimizer that shifts update energy away from weight rows whose recent gradients conflict with the longer-term trend, reaching NorMuon’s loss with 1.07–1.10x higher token efficiency from 130M to 1.1B parameters at under 5% extra wall-clock time.
GraphFuse-R1: A Compiler-Side Bound and a Learned Graph-Level Policy for Operator Fusion
Published in Under review, 2026
Under review. GraphFuse-R1 trains an 8B LLM with SFT and GRPO to propose whole-graph operator-fusion groups inside PyTorch’s TorchInductor, compiling 28.5% fewer kernels and fusing 39% more nodes than the hand-written heuristic, and derives a compiler-side bound on how much fusion headroom remains.
Syntactic Prediction through Reinforcement Learning
Published in Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026), Main Conference, 2026
Accepted to EMNLP 2026 (Main Conference). Syntax-R1 is a two-stage post-training framework that uses reinforcement learning to improve hierarchical syntactic prediction in large language models, achieving state-of-the-art results on constituency parsing and CCG supertagging.
HR-Merge: Model Merging with Headroom-Weighted Residual Refinement
Published in NeurIPS 2026 Workshop on Neural Artifacts (NeuralArtifacts), Poster, 2026
NeurIPS 2026 NeuralArtifacts Workshop (Poster). A training-free, merge-operator-agnostic wrapper that provably never underperforms the base merge on validation. It gives the best result in every CLIP ViT and LoRA setting tested, reaching 94.29 on the LLaMA-3 8B six-NLI benchmark.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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