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Found 15 papers, 9 papers with code
How ChatGPT is Solving Vulnerability Management Problem
Prior works show that ChatGPT has the capabilities of processing foundational code analysis tasks, such as abstract syntax tree generation, which indicates the potential of using ChatGPT to comprehend code syntax and static behaviors.
Relation Extraction Model Based on Semantic Enhancement Mechanism
The CasAug model proposed in this paper based on the CasRel framework combined with the semantic enhancement mechanism can solve this problem to a certain extent.
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.
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study
Different from previous studies focused on overall performance, this work aims to investigate the impact of quantization on \emph{emergent abilities}, which are important characteristics that distinguish LLMs from small language models.
A semantically enhanced dual encoder for aspect sentiment triplet extraction
Aspect sentiment triplet extraction (ASTE) is a crucial subtask of aspect-based sentiment analysis (ABSA) that aims to comprehensively identify sentiment triplets.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
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.
A Survey of Large Language Models
To discriminate the difference in parameter scale, the research community has coined the term large language models (LLM) for the PLMs of significant size.
Scaling Pre-trained Language Models to Deeper via Parameter-efficient Architecture
Based on such a decomposition, our architecture shares the central tensor across all layers for reducing the model size and meanwhile keeps layer-specific auxiliary tensors (also using adapters) for enhancing the adaptation flexibility.
TikTalk: A Video-Based Dialogue Dataset for Multi-Modal Chitchat in Real World
Experimental results indicate that the models incorporating large language models (LLM) can generate more diverse responses, while the model utilizing knowledge graphs to introduce external knowledge performs the best overall.
Bi-convolution matrix factorization algorithm based on improved ConvMF
With the rapid development of information technology, "information overload" has become the main theme that plagues people's online life.
WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models
The results show that WuDaoMM can be applied as an efficient dataset for VLPMs, especially for the model in text-to-image generation task.
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models
Recently, Mixture-of-Experts (short as MoE) architecture has achieved remarkable success in increasing the model capacity of large-scale language models.
Image Dataset Compression Based on Matrix Product States
Based on the MPS structure, we propose a new dataset compression method that compresses datasets by filtering long-range correlation information in task-agnostic scenarios and uses dataset distillation to supplement the information in task-specific scenarios.
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators
This paper presents a novel pre-trained language models (PLM) compression approach based on the matrix product operator (short as MPO) from quantum many-body physics.
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
We further construct a large Chinese multi-source image-text dataset called RUC-CAS-WenLan for pre-training our BriVL model.
Ranked #1 on
Image Retrieval
on RUC-CAS-WenLan
