Search Results for author:
Found 6 papers, 4 papers with code
AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection
Code Clone Detection, which aims to retrieve functionally similar programs from large code bases, has been attracting increasing attention.
CP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code
Automatically generating function summaries for binaries is an extremely valuable but challenging task, since it involves translating the execution behavior and semantics of the low-level language (assembly code) into human-readable natural language.
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization
In this paper, we propose a fine-grained Token-level retrieval-augmented mechanism (Tram) on the decoder side rather than the encoder side to enhance the performance of neural models and produce more low-frequency tokens in generating summaries.
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning
Towards real-world information extraction scenario, research of relation extraction is advancing to document-level relation extraction(DocRE).
Ranked #25 on
Relation Extraction
on DocRED
MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks
For plasticity, we propose a trainable convolutional synapse that models spike response current to enhance the diversity of spiking neurons for temporal feature extraction.
Ranked #6 on
Audio Classification
on SHD
Constructing Contrastive samples via Summarization for Text Classification with limited annotations
Unlike vision tasks, the data augmentation method for contrastive learning has not been investigated sufficiently in language tasks.
