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08/21/2023
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents
Autonomous agents empowered by Large Language Models (LLMs) have undergo...
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08/15/2023
Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation
Personalized recommendation relies on user historical behaviors to provi...
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07/31/2023
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Despite the advancements of open-source large language models (LLMs) and...
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05/28/2023
Emergent Modularity in Pre-trained Transformers
This work examines the presence of modularity in pre-trained Transformer...
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05/15/2023
Large Language Models are Zero-Shot Rankers for Recommender Systems
Recently, large language models (LLMs) (e.g. GPT-4) have demonstrated im...
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05/15/2023
Recyclable Tuning for Continual Pre-training
Continual pre-training is the paradigm where pre-trained language models...
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05/11/2023
Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
In the past decades, recommender systems have attracted much attention i...
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05/11/2023
WebCPM: Interactive Web Search for Chinese Long-form Question Answering
Long-form question answering (LFQA) aims at answering complex, open-ende...
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05/06/2023
Attacking Pre-trained Recommendation
Recently, a series of pioneer studies have shown the potency of pre-trai...
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04/11/2023
Triple Sequence Learning for Cross-domain Recommendation
Cross-domain recommendation (CDR) aims to leverage the users' behaviors ...
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03/21/2023
A Survey on Causal Inference for Recommendation
Recently, causal inference has attracted increasing attention from resea...
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02/05/2023
Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation
Recently, Graph Neural Networks (GNNs) achieve remarkable success in Rec...
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11/22/2022
Visually Grounded Commonsense Knowledge Acquisition
Large-scale commonsense knowledge bases empower a broad range of AI appl...
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10/09/2022
Improve Transformer Pre-Training with Decoupled Directional Relative Position Encoding and Representation Differentiations
In this work, we revisit the Transformer-based pre-trained language mode...
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09/19/2022
Reweighting Clicks with Dwell Time in Recommendation
The click behavior is the most widely-used user positive feedback in rec...
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07/04/2022
Multi-granularity Item-based Contrastive Recommendation
Contrastive learning (CL) has shown its power in recommendation. However...
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06/30/2022
Customized Conversational Recommender Systems
Conversational recommender systems (CRS) aim to capture user's current i...
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05/23/2022
Prompt Tuning for Discriminative Pre-trained Language Models
Recent works have shown promising results of prompt tuning in stimulatin...
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05/19/2022
Personalized Prompts for Sequential Recommendation
Pre-training models have shown their power in sequential recommendation....
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05/10/2022
Selective Fairness in Recommendation via Prompts
Recommendation fairness has attracted great attention recently. In real-...
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04/20/2022
User-Centric Conversational Recommendation with Multi-Aspect User Modeling
Conversational recommender systems (CRS) aim to provide highquality reco...
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03/20/2022
Multi-view Multi-behavior Contrastive Learning in Recommendation
Multi-behavior recommendation (MBR) aims to jointly consider multiple be...
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12/02/2021
Contrastive Cross-domain Recommendation in Matching
Cross-domain recommendation (CDR) aims to provide better recommendation ...
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10/22/2021
MIC: Model-agnostic Integrated Cross-channel Recommenders
Semantically connecting users and items is a fundamental problem for the...
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10/21/2021
Personalized Transfer of User Preferences for Cross-domain Recommendation
Cold-start problem is still a very challenging problem in recommender sy...
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09/30/2021
USER: A Unified Information Search and Recommendation Model based on Integrated Behavior Sequence
Search and recommendation are the two most common approaches used by peo...
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05/31/2021
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising
In recommender systems and advertising platforms, marketers always want ...
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05/11/2021
Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks
Recently, embedding techniques have achieved impressive success in recom...
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05/11/2021
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users
Cold-start problems are enormous challenges in practical recommender sys...
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02/22/2021
UPRec: User-Aware Pre-training for Recommender Systems
Existing sequential recommendation methods rely on large amounts of trai...
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02/07/2021
Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network
Recently, real-world recommendation systems need to deal with millions o...
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11/08/2020
Denoising Relation Extraction from Document-level Distant Supervision
Distant supervision (DS) has been widely used to generate auto-labeled d...
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09/19/2020
Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect
Recommender systems aim to provide item recommendations for users, and a...
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07/21/2020
Connecting Embeddings for Knowledge Graph Entity Typing
Knowledge graph (KG) entity typing aims at inferring possible missing en...
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11/14/2019
FAQ-based Question Answering via Knowledge Anchors
Question answering (QA) aims to understand user questions and find appro...
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08/29/2019
Neural Snowball for Few-Shot Relation Learning
Knowledge graphs typically undergo open-ended growth of new relations. T...
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12/28/2018
Knowledge Representation Learning: A Quantitative Review
Knowledge representation learning (KRL) aims to represent entities and r...
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10/29/2018
Language Modeling with Sparse Product of Sememe Experts
Most language modeling methods rely on large-scale data to statistically...
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06/17/2018
Incorporating Chinese Characters of Words for Lexical Sememe Prediction
Sememes are minimum semantic units of concepts in human languages, such ...
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05/09/2017
Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence
Knowledge graphs (KGs) can provide significant relational information an...
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12/14/2016
Neural Emoji Recommendation in Dialogue Systems
Emoji is an essential component in dialogues which has been broadly util...
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09/22/2016
