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50 papers match

cs.LG2026

S-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring

Glenn Anta Bucagu, Thorir Mar Ingolfsson, Yawei Li +1

The paper introduces S-CEReBrO, a streaming Transformer architecture that uses a windowed alternating attention mechanism to keep memory usage constant during continuous EEG monito…

#eeg analysis#continuous monitoring#transformer models#attention mechanisms
cs.IR2026

CCFormer: Efficient Cross-Field Interaction and Hierarchical Sequence Compression for Industrial Recommendation at Tencent

Yunlong Wang, Huizhe Zhang, Haonan Hu +5

The paper introduces CCFormer, an efficient Transformer architecture that combines cross-field attention with hierarchical sequence compression to improve industrial recommendation…

#recommender systems#transformer models#cross-field attention#sequence compression
cs.RO2026

Arm2Air: Cross-Embodiment Skeleton Transfer for 3D Relay Formation

Dohun Lee, Kyeonghyun Yoo, Seokmin Kim +3

The paper introduces Arm2Air, a method that transfers obstacle-avoidance motion skeletons learned from robot arms to UAVs for efficient 3D relay placement in cluttered urban enviro…

#uav relay placement#cross-embodiment transfer#skeleton planning#transformer models
cs.AI2026

MUL-T: Decoding Spatial Cellular Architecture in Multiplexed Tissue Images

Farzaneh Seyedshahi, Kai Rakovic, Adalberto Claudio Quiros +2

The paper introduces MUL-T, a lightweight transformer that models spatial cellular architecture in multiplexed tissue images by predicting masked cell tokens, achieving strong perf…

#multiplexed tissue imaging#spatial cellular architecture#transformer models#masked contextual prediction
cs.LG2026

LM-GRASP: Instance-Specific Language Models for Combinatorial Construction via Online Imitation Learning

Mohand Mezmaz, Grégoire Danoy

The paper introduces LM-GRASP, a method that trains a Transformer-based construction policy online for each combinatorial optimization instance using imitation learning from a loca…

#combinatorial optimization#metaheuristics#imitation learning#transformer models
cs.CL2026

Causal Discovery with Inverted Self-attention for Multivariate Time Series

Yusen Liu, Yong Wang, Yifan Yin +3

The paper introduces a transformer-based framework that uses an inverted self‑attention mechanism to uncover causal relationships in multivariate time series, emphasizing indirect…

#causal discovery#time series analysis#self-attention#transformer models