SIGIR 2024 M1.6 [fp] Large Language Models for Intent-Driven Session Recommendations

SIGIR 2024 M1.6 [fp] Sequential Recommendation with Latent Relations based on Large Language ModelПодробнее

SIGIR 2024 M1.1 [fp] CorpusLM: Towards Unified Language Model on Corpus for Knowledge-Intensive TaskПодробнее

SIGIR 2024 M3.5 [fp] Adaptive In-Context Learning with Large Language Models for Bundle GenerationПодробнее

SIGIR 2024 W1.1 [fp] I3: Intent-Introspective Retrieval Conditioned on InstructionsПодробнее

SIGIR 2024 M1.6 [fp] Reinforcement Learning-based Recommender Systems with LLMsПодробнее

SIGIR 2024 M1.6 [fp] IDGenRec: LLM-RecSys Alignment with Textual ID LearningПодробнее

SIGIR 2024 M1.6 [fp] Enhancing Sequential Recommenders with Augmented Knowledge from Aligned LLMsПодробнее

SIGIR 2024 T2.5 [fp] Let Me Do It For You: Towards LLM Empowered Recommendation via Tool LearningПодробнее

SIGIR 2024 M1.6 [**rr] OpenP5: Open-Source Platform for Developing, Training, & Evaluating LLM RSПодробнее

SIGIR 2024 M1.5 [fp] Uncontextualized significance considered dangerousПодробнее

SIGIR 2024 M3.2 [fp] LAPS: LLM-Augmented Dialogue Construction for Personalized Multi-Session CSПодробнее

SIGIR 2024 T2.5 [fp] LLaRA: Large Language-Recommendation AssistantПодробнее

SIGIR 2024 M1.3 [fp] Neural Passage Quality Estimation for Static PruningПодробнее

SIGIR 2024 M1.1 [fp] Setwise Approach for Effective & Highly Efficient Zero-shot Ranking with LLMsПодробнее

SIGIR 2024 M2.4 [fp] Steering Large Language Models for Cross-lingual Information RetrievalПодробнее

SIGIR 2024 M3.6 [fp] UniSAR: Modeling User Transition Behaviors between Search and RecommendationПодробнее

SIGIR 2024 M3.5 [fp] AutoDCS: Automated Decision Chain Selection in Deep Recommender SystemsПодробнее

SIGIR 2024 W1.3 [fp] Large Language Models can Accurately Predict Searcher PreferencesПодробнее

SIGIR 2024 M1.3 [rr] Ranked List Truncation for Large Language Model-based Re-RankingПодробнее