3 papers
cs.CL2026
Q-Interference: Memory-Efficient Phase-Aware Quantum-Inspired Attention
Emama Nahid, Tahmid Imtiaz Imu, Huayue Gu +3
GPT attention measures token compatibility through dot-product similarity. This mechanism is simple, effective, and memory-efficient. But it does not explicitly model whether stron…
cs.LG2026
Approximate Subgraph Matching with Neural Graph Representations and Reinforcement Learning
Kaiyang Li, Shihao Ji, Zhipeng Cai +1
Approximate subgraph matching (ASM) is a task that determines the approximate presence of a given query graph in a large target graph. Being an NP-hard problem, ASM is critical in…
cs.LG2025
Uni-LoRA: One Vector is All You Need
Kaiyang Li, Shaobo Han, Qing Su +3
Low-Rank Adaptation (LoRA) has become the de facto parameter-efficient fine-tuning (PEFT) method for large language models (LLMs) by constraining weight updates to low-rank matrice…