[ACL 2024] Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models

The implementation for the Recsys paper: Towards Empathetic Conversational Recommender System

This paper list focuses on the theoretical and empirical analysis of language models, especially large language models (LLMs). The papers in this list investigate the learning behavior, generalizat…

Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation

[SIGIR'24] Generative Retrieval as Multi-Vector Dense Retrieval

Learning to Tokenize for Generative Retrieval (NeurIPS 2023)

Rate the news.

[WSDM 2024 best paper honorable mention] Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure

山东大学硕/博士研究生毕业论文模板

Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

夫子•明察司法大模型是由山东大学、浪潮云、中国政法大学联合研发，以 ChatGLM 为大模型底座，基于海量中文无监督司法语料与有监督司法微调数据训练的中文司法大模型。该模型支持法条检索、案例分析、三段论推理判决以及司法对话等功能，旨在为用户提供全方位、高精准的法律咨询与解答服务。

Papers & Works for large languange models (OpenAI GPT-4, Meta Llama, etc.).

Universal and Transferable Attacks on Aligned Language Models

A 13B large language model developed by Baichuan Intelligent Technology

dataset for paper Reference-Assisted Dialogue Evaluation for Open-Domain Dialogue.

中文法律LLaMA (LLaMA for Chinese legel domain)

Code for ACL 2023 findings paper "UMSE: Unified Multi-scenario Summarization Evaluation"

Code for ACL 2023 paper "Dialogue Summarization with Structure-aware Graph Modeling via Static-Dynamic Fused Graph"

Large Language Model-enhanced Recommender System Papers

SuperCLUE: 中文通用大模型综合性基准 | A Benchmark for Foundation Models in Chinese

🦜🔗 Build context-aware reasoning applications

LlamaIndex is the leading framework for building LLM-powered agents over your data.

The official GitHub page for the survey paper "A Survey of Large Language Models".

[TOIS 2023] On the User Behavior Leakage from Recommender System Exposure