Search Results for author:
Found 9 papers, 5 papers with code
MCA: Moment Channel Attention Networks
In this paper, we investigate the statistical moments of feature maps within a neural network.
ML-Bench: Evaluating Large Language Models for Code Generation in Repository-Level Machine Learning Tasks
While Large Language Models (LLMs) have demonstrated proficiency in code generation benchmarks, translating these results into practical development scenarios - where leveraging existing repository-level libraries is the norm - remains challenging.
Reconfigurable Intelligent Surface & Edge -- An Introduction of an EM manipulation structure on obstacles' edge
In this paper, Reconfigurable Intelligent Surface & Edge (RISE) is proposed to extend RIS' abilities of reflection and refraction over surfaces to diffraction around obstacles' edge for better adaptation to specific coverage scenarios.
Unifying Token and Span Level Supervisions for Few-Shot Sequence Labeling
However, these methods are only trained at a single granularity (i. e., either token level or span level) and have some weaknesses of the corresponding granularity.
Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning
For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes.
Learning to Classify Open Intent via Soft Labeling and Manifold Mixup
In our method, soft labeling is used to reshape the label distribution of the known intent samples, aiming at reducing model's overconfident on known intents.
A Symmetric Local Search Network for Emotion-Cause Pair Extraction
Each subnetwork is composed of a clause representation learner and a local pair searcher.
Enriching Word Embeddings with Domain Knowledge for Readability Assessment
In this paper, we present a method which learns the word embedding for readability assessment.
