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Showing papers from Northerstern University Show all papers

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NeurIPS 2026NortheasternNortheast University at QinhuangShandongNortheastern University, ChinaNorthersternInstruction tuning

SMoA: Spectrum Modulation Adapter for Parameter-Efficient Fine-Tuning

SMoA modulates spectra via block-diagonal Hadamard low-rank branches to expand representational coverage under small parameter budgets, outperforming LoRA on multiple tasks.

Yongkang Liu, Xing Li, Mengjie Zhao, Shanru Zhang and 6 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 5/10
strict 1/5
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NeurIPS 2026NortheasternShanghai Jiao TongU MunichShandongNorthersternInstruction tuning

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning

ChunkFT enables memory-efficient full-parameter fine-tuning via dynamically activated sub-tensors, cutting 7B model memory to 13.72GB and outperforming baselines.

Yongkang Liu, Zijing Wang, Mengjie Zhao, Ercong Nie and 6 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5