1 citations · 1 across the 3 of their papers we have counts for
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ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
Jianan Nie, Peiyao Xiao, Kaiyi Ji +1
Predicting properties of crystals from their structures is a fundamental yet challenging task in materials science. Unlike molecules, crystal structures exhibit infinite periodic a…
Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs
Hao Ban, Kaiyi Ji
Large language models are often adapted using parameter-efficient techniques such as Low-Rank Adaptation (LoRA), formulated as , where is the pre-trained para…
DeepMTL2R: A Library for Deep Multi-task Learning to Rank
Chaosheng Dong, Peiyao Xiao, Yijia Wang +1
This paper presents DeepMTL2R, an open-source deep learning framework for Multi-task Learning to Rank (MTL2R), where multiple relevance criteria must be optimized simultaneously. D…
LDC-MTL: Balancing Multi-Task Learning through Scalable Loss Discrepancy Control
Peiyao Xiao, Chaosheng Dong, Shaofeng Zou +1
Multi-task learning (MTL) has been widely adopted for its ability to simultaneously learn multiple tasks. While existing gradient manipulation methods often yield more balanced sol…
SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation
Hao Ban, Gokul Ram Subramani, Kaiyi Ji
Multi-task learning (MTL) enables a joint model to capture commonalities across multiple tasks, reducing computation costs and improving data efficiency. However, a major challenge…
MGDA Converges under Generalized Smoothness, Provably
Qi Zhang, Peiyao Xiao, Shaofeng Zou +1
Multi-objective optimization (MOO) is receiving more attention in various fields such as multi-task learning. Recent works provide some effective algorithms with theoretical analys…