CRAMER: Control via Request-Aware Masking for Editing Recommenders
cs.IR, cs.AI, cs.LG
Submitted: 2026-08-26
Updated: 2026-09-13
Code: https://github.com/zhiyuansu0326/CRAMER-ICML2026
Terminology
Sources
- Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
- A Survey on Multi-Behavior Sequential Recommendation
- Categorical Reparameterization with Gumbel-Softmax
- The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
- Attention Is Not All You Need: The Importance of Feedforward Networks in Transformer Models
- Transformer Feed-Forward Layers Are Key-Value Memories
- Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders
- Posterior Control of Blackbox Generation
- Eliminating Out-of-Domain Recommendations in LLM-based Recommender Systems: A Unified View
- On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers
- A Survey on Sequential Recommendation
- Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval
- Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
- RoBERTa: A Robustly Optimized BERT Pretraining Approach
- Learning Sparse Neural Networks through $L_0$ Regularization
- The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
- Intent Recognition in Conversational Recommender Systems
- Enhancing Latent Computation in Transformers with Latent Tokens
- FineGates: LLMs Finetuning with Compression using Stochastic Gates
- REARANK: Reasoning Re-ranking Agent via Reinforcement Learning
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