Top Tweets for #RecSys
Recommendation latest research progress | 9. LoKA: Low-precision Kernel Applications for Recommendation Models At Scale
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 8. Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 7. L2Rec: Towards Dual-View Understanding of LLMs for Personalized Recommendation
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 6. Beyond Static Best-of-N: Bayesian List-wise Alignment for LLM-based Recommendation
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 5. Just Ask for a Table: A Thirty-Token User Prompt Defeats Sponsored Recommendations in Twelve LLMs
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 4. MuChator: Enabling Active Music Discovery via Conversational Music LLMs in Douyin Music
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 3. RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 2. Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled Trial
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 1. RcLLM: Accelerating Generative Recommendation via Beyond-Prefix KV Caching
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
π Two papers at #SIGIR2026!
π± CATS: Clustering + Thompson Sampling for smarter negative mining in RecSys. +20% NDCG@10.
βοΈ Load-sensitive Selective Pruning: dynamic embedding dimensionality for dense retrieval under load. +400% queries served.
See you in Melbourne! #IR #RecSys
@IntRSworkshop at #RecSys2026
The Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
at
RecSys 2026 in Minneapolis
September 27 - October 2, 2026
π
Papers due: July 20th, 2026
#RecSys #Interaction #DecisionMaking
https://t.co/VltvYoXnlS
Using Reviews to Create a #RecSys That Works. #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
https://t.co/chceDmHs5l
What % of the NLP papers measure their impact in the real world? This paper proposes an "impact evaluation" of NLP models or systems for real-world usage, changing the research culture of NLP to focus more on real-world
impact and less on SOTA-chasing: https://t.co/3Ti5vUgdgs
Recommendation latest research progress | 10. CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 9. Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 8. Seeing Further and Wider: Joint Spatio-Temporal Enlargement for Micro-Video Popularity Prediction
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
Recommendation latest research progress | 7. Signal or Noise in Multi-Agent LLM-based Stock Recommendations?
#AI #DeepLearning #ArtificialInteligence #Datascience #Research #recsys
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