https://github.com/Meow-E/USimAgent2.0
공식 코드Exploring Human-Like Thinking in Search Simulations with Large Language Models
Papers with Code 아카이브
User Simulation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
Simulation of user interacting with a dialog system
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MiuLab/UserSimulator
공식 코드https://github.com/alcein/taira
공식 코드Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent
https://github.com/chongminggao/KuaiRec
공식 코드KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems
https://github.com/danialebrat/lusifer
공식 코드Lusifer: LLM-based User SImulated Feedback Environment for online Recommender systems
https://github.com/diligentspring/investigating-the-robustness-of-counterfactual-learning-to-rank-models
공식 코드Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
https://github.com/iai-group/ictir2024-usersim-objectives
공식 코드Towards a Formal Characterization of User Simulation Objectives in Conversational Information Access
https://github.com/iai-group/kdd2020-usersim
공식 코드Evaluating Conversational Recommender Systems via User Simulation
https://github.com/iai-group/sigir2022-usersim
공식 코드Analyzing and Simulating User Utterance Reformulation in Conversational Recommender Systems
https://github.com/iai-group/usersimcrs
공식 코드UserSimCRS: A User Simulation Toolkit for Evaluating Conversational Recommender Systems
https://github.com/isekulic/usi
공식 코드Evaluating Mixed-initiative Conversational Search Systems via User Simulation
https://github.com/kaniblu/vhda
공식 코드Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation
https://github.com/lanyu0303/afl
공식 코드Agentic Feedback Loop Modeling Improves Recommendation and User Simulation
https://github.com/meow-e/usimagent
공식 코드USimAgent: Large Language Models for Simulating Search Users
https://github.com/nob0/crs-breakdown-detection
공식 코드Identifying Breakdowns in Conversational Recommender Systems using User Simulation
https://github.com/rafaelhferreira/mtad_cta
공식 코드Multi-trait User Simulation with Adaptive Decoding for Conversational Task Assistants
https://github.com/ruc-gsai/yulan-rec
공식 코드User Behavior Simulation with Large Language Model based Agents
https://github.com/salesforce/botsim
공식 코드BotSIM: An End-to-End Bot Simulation Toolkit for Commercial Task-Oriented Dialog Systems
https://github.com/sunnweiwei/user-satisfaction-simulation
공식 코드Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue Systems
https://github.com/telepathylabsai/prompt-based-user-simulator
공식 코드In-Context Learning User Simulators for Task-Oriented Dialog Systems
https://github.com/thu-coai/CrossWOZ
공식 코드CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
https://github.com/verena-hallitschke/pet-ct-annotate
공식 코드https://github.com/wyshi/user-simulator
공식 코드How to Build User Simulators to Train RL-based Dialog Systems
https://github.com/xymou/social_simulation
공식 코드https://github.com/Ambitioner-c/UserSimulator
https://github.com/AtmaHou/UserSimulator
https://github.com/MiuLab/TC-Bot
https://github.com/Zhihan1996/User-sim
https://github.com/chongminggao/cirs-codes
KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems
https://github.com/dirtdust/TC-Bot-python3
https://github.com/durashi/Dialog_policy_network_for_low_resource_setting
https://github.com/fighting41love/funNLP
CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
https://github.com/jerrylsu/TC-Bot
https://github.com/markWJJ/TC-Bot
https://github.com/mengyuest/reactive_cbf
Reactive and Safe Road User Simulations using Neural Barrier Certificates
https://github.com/silviatti/prompt-based-user-simulator
In-Context Learning User Simulators for Task-Oriented Dialog Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.