Search Results for author:
Found 15 papers, 3 papers with code
GenSERP: Large Language Models for Whole Page Presentation
(2) An answer generation phase where the LLM populates the layouts with the retrieved content.
MART: Improving LLM Safety with Multi-round Automatic Red-Teaming
Specifically, an adversarial LLM and a target LLM interplay with each other in an iterative manner, where the adversarial LLM aims to generate challenging prompts that elicit unsafe responses from the target LLM, while the target LLM is fine-tuned with safety aligned data on these adversarial prompts.
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
In this study, we introduce adaptive KV cache compression, a plug-and-play method that reduces the memory footprint of generative inference for Large Language Models (LLMs).
Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories
In this paper we improve the zero-shot generalization ability of language models via Mixture-Of-Memory Augmentation (MoMA), a mechanism that retrieves augmentation documents from multiple information corpora ("external memories"), with the option to "plug in" new memory at inference time.
Toward Understanding Bias Correlations for Mitigation in NLP
In particular, we examine bias mitigation in two common NLP tasks -- toxicity detection and word embeddings -- on three social identities, i. e., race, gender, and religion.
Unsupervised Multi-Granularity Summarization
In this paper, we propose the first unsupervised multi-granularity summarization framework, GranuSum.
Fine-Grained Opinion Summarization with Minimal Supervision
Opinion summarization aims to profile a target by extracting opinions from multiple documents.
Improving Cyberbully Detection with User Interaction
Cyberbullying, identified as intended and repeated online bullying behavior, has become increasingly prevalent in the past few decades.
Graph Enhanced Representation Learning for News Recommendation
Existing news recommendation methods achieve personalization by building accurate news representations from news content and user representations from their direct interactions with news (e. g., click), while ignoring the high-order relatedness between users and news.
FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning
Since the labeled data in different platforms usually has some differences in entity type and annotation criteria, instead of constraining different platforms to share the same model, we decompose the medical NER model in each platform into a shared module and a private module.
Neural News Recommendation with Multi-Head Self-Attention
The core of our approach is a news encoder and a user encoder.
Reviews Meet Graphs: Enhancing User and Item Representations for Recommendation with Hierarchical Attentive Graph Neural Network
In the review content-view, we propose to use a hierarchical model to first learn sentence representations from words, then learn review representations from sentences, and finally learn user/item representations from reviews.
Detecting and Extracting of Adverse Drug Reaction Mentioning Tweets with Multi-Head Self Attention
This paper describes our system for the first and second shared tasks of the fourth Social Media Mining for Health Applications (SMM4H) workshop.
THU\_NGN at SemEval-2019 Task 3: Dialog Emotion Classification using Attentional LSTM-CNN
With the development of the Internet, dialog systems are widely used in online platforms to provide personalized services for their users.
THU\_NGN at SemEval-2019 Task 12: Toponym Detection and Disambiguation on Scientific Papers
First name: Tao Last name: Qi Email: taoqi. qt@gmail. com Affiliation: Department of Electronic Engineering, Tsinghua University First name: Suyu Last name: Ge Email: gesy17@mails. tsinghua. edu. cn Affiliation: Department of Electronic Engineering, Tsinghua University First name: Chuhan Last name: Wu Email: wuch15@mails. tsinghua. edu. cn Affiliation: Department of Electronic Engineering, Tsinghua University First name: Yubo Last name: Chen Email: chen-yb18@mails. tsinghua. edu. cn Affiliation: Department of Electronic Engineering, Tsinghua University First name: Yongfeng Last name: Huang Email: yfhuang@mail. tsinghua. edu. cn Affiliation: Department of Electronic Engineering, Tsinghua University Toponym resolution is an important and challenging task in the neural language processing field, and has wide applications such as emergency response and social media geographical event analysis.
