PPaperPicks

Ruiming Tang

74 papers at tracked venues · 50 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. DARL: Encouraging Diverse Answers for General Reasoning without Verifiers
  2. DPWriter: Reinforcement Learning with Diverse Planning Branching for Creative Writing
  3. DeepSynth-Eval: Objectively Evaluating Information Consolidation in Deep Survey Writing
  4. DiffGRM: Diffusion-based Generative Recommendation Model
  5. Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement Learning
  6. Exploring Recommender System Evaluation: A Multi-Modal LLM Agent Framework for A/B Testing
  7. GRank: Towards Target-Aware and Streamlined Industrial Retrieval with a Generate-Rank Framework
  8. MGFRec: Towards Reinforced Reasoning Recommendation with Multiple Groundings and Feedback
  9. Modular Representation Compression: Adapting LLM Representations for Efficient and Effective Recommendation
  10. OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service
  11. OneRec-Think: In-Text Reasoning for Generative Recommendation
  12. RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation
  13. ToolACE-R: Model-aware Iterative Training and Adaptive Refinement for Tool learning
  14. Unleashing the Native Recommendation Potential: LLM-Based Generative Recommendation via Structured Term Identifiers
  15. Action First: Leveraging Preference-Aware Actions for More Effective Decision-Making in Interactive Recommender Systems
  16. Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger
  17. AdvKT: An Adversarial Multi-step Training Framework for Knowledge Tracing
  18. An Automatic Graph Construction Framework based on Large Language Models for Recommendation
  19. Benchmarking Retrieval-Augmented Multimomal Generation for Document Question Answering
  20. Boost, Disentangle, and Customize: A Robust System2-to-System1 Pipeline for Code Generation
  21. Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation
  22. Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization
  23. CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehension
  24. CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
  25. CodePRM: Execution Feedback-enhanced Process Reward Model for Code Generation
  26. Crowd Comparative Reasoning: Unlocking Comprehensive Evaluations for LLM-as-a-Judge
  27. DebateCoder: Towards Collective Intelligence of LLMs via Test Case Driven LLM Debate for Code Generation
  28. Efficiency Unleashed: Inference Acceleration for LLM-based Recommender Systems with Speculative Decoding
  29. FuXi-α: Scaling Recommendation Model with Feature Interaction Enhanced Transformer
  30. Generative Large Recommendation Models: Emerging Trends in LLMs for Recommendation
  31. Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?
  32. HyperGate: Hierarchical Perceptive Gating Network for Multi-domain Multi-task Recommendation
  33. Instruction-Tuning Data Synthesis from Scratch via Web Reconstruction
  34. Joint Modeling in Deep Recommender Systems
  35. LLM4CD: Leveraging Large Language Models for Open-World Knowledge Augmented Cognitive Diagnosis
  36. LLM4Rerank: LLM-based Auto-Reranking Framework for Recommendations
  37. LLM4Tag: Automatic Tagging System for Information Retrieval via Large Language Models
    SIGKDD 2025 · Ruiming Tang
  38. LSRP: A Leader-Subordinate Retrieval Framework for Privacy-Preserving Cloud-Device Collaboration
  39. MMDocIR: Benchmarking Multimodal Retrieval for Long Documents
  40. MTRec: Learning to Align with User Preferences via Mental Reward Models
  41. NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging
  42. P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models
  43. Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning
  44. Prompt Tuning as User Inherent Profile Inference Machine
  45. RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation
  46. RethinkMCTS: Refining Erroneous Thoughts in Monte Carlo Tree Search for Code Generation
  47. RevisEval: Improving LLM-as-a-Judge via Response-Adapted References
  48. SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems
  49. SampleLLM: Optimizing Tabular Data Synthesis in Recommendations
  50. Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark
  51. ToolACE: Winning the Points of LLM Function Calling
  52. AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising
  53. ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
  54. D3: A Methodological Exploration of Domain Division, Modeling, and Balance in Multi-Domain Recommendations
  55. Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation
  56. DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
  57. ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation
  58. ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
  59. FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
  60. HiFI: Hierarchical Fairness-aware Integrated Ranking with Constrained Reinforcement Learning
  61. HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations
  62. IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation
  63. LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation
  64. Learning to Edit: Aligning LLMs with Knowledge Editing
  65. LightCS: Selecting Quadratic Feature Crosses in Linear Complexity
  66. M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation
  67. MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
  68. Ranking-Aware Unbiased Post-Click Conversion Rate Estimation via AUC Optimization on Entire Exposure Space
  69. ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
  70. Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data
  71. Retrieval-Oriented Knowledge for Click-Through Rate Prediction
  72. SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model
  73. Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
  74. User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation