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Unveiling Knowledge Utilization Mechanisms in LLM-based Retrieval-Augmented Generation
Search-Based Interaction For Conversation Recommendation via Generative Reward Model Based Simulated User
LLM-based Search Assistant with Holistically Guided MCTS for Intricate Information Seeking
Generative Recommender with End-to-End Learnable Item Tokenization
UFIN: Universal Feature Interaction Network for Multi-Domain Click-Through Rate Prediction
Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment
NPTI:Neuron Based Personality Trait Induction in Large Language Models
Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning
DAWN-ICL: Strategic Planning of Problem-solving Trajectories for Zero-Shot In-Context Learning
RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement
Frequency-Augmented Mixture-of-Heterogeneous-Experts Framework for Sequential Recommendation
Self-Calibrated Listwise Reranking with Large Language Models
Unleashing the Potential of Large Language Models as Prompt Optimizers: An Analogical Analysis with Gradient-based Model Optimizers
发表论文:任瑞阳同学论文被 LREC-COLING 2025 录用
Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation
发表论文:都一凡同学论文被 LREC-COLING 2025 录用
What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning
JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
Exploring Context Window of Large Language Models via Decomposed Positional Vectors
Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models
Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector
REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-domain Question Answering
Not Everything is All You Need: Toward Low-Redundant Optimization for Large Language Model Alignment
BASES: Large-scale Web Search User Simulation with Large Language Model based Agents
Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models
AuriSRec: Adversarial User Intention Learning in Sequential Recommendation
Scaling Law of Large Sequential Recommendation Models
Promoting Two-sided Fairness with Adaptive Weights for Providers and Customers in Recommendation
Rotative Factorization Machines
Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method
The dawn after the dark: An empirical study on factuality hallucination in large language models
Language-specific neurons: The key to multilingual capabilities in large language models
Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression
Data-CUBE: Data Curriculum for Instruction-based Sentence Representation Learning
Improving large language models via fine-grained reinforcement learning with minimum editing constraint
LLMBox: A Comprehensive Library for Large Language Models
Sequence-level Semantic Representation Fusion for Recommender Systems
EulerFormer: Sequential User Behavior Modeling With Complex Vector Attention
Privacy-Preserving Cross-Domain Recommendation With Federated Graph Learning
Adapting Large Language Models By Integrating Collaborative Semantics For Recommendation
Not All Metrics Are Guilty: Improving NLG Evaluation By Diversifying References
发表论文:成晓雪同学论文被 LREC-COLING 2024 录用
ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting
发表论文:董梓灿同学论文被 LREC-COLING 2024 录用
BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models
发表论文:刘沛羽同学论文被 LREC-COLING 2024 录用
Enhancing Parameter-efficient Fine-tuning with Simple Calibration based on Stable Rank
发表论文:刘沛羽同学论文被 LREC-COLING 2024 录用
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study
AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems
Dense Text Retrieval based on Pretrained Language Models: A Survey
Evaluating Object Hallucination In Large Vision-Language Models
HaluEval: A Large-Scale Hallucination Evaluation Benchmark For Large Language Models
Rethinking The Evaluation For Conversational Recommendation In The Era Of Large Language Models
StructGPT: A General Framework For Large Language Model To Reason Over Structured Data
ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph
Enhancing Scalability Of Pre-Trained Language Models Via Efficient Parameter Sharing
A Thorough Examination On Zero-Shot Dense Retrieval
ChatCoT: Tool-Augmented Chain-Of-Thought Reasoning On Chat-Based Large Language Models
Evaluating And Improving Tool-Augmented Computation-Intensive Math Reasoning
发表论文:周昆同学论文被 ECML-PKDD 2023 录用
MASTER: Multi-Task Pre-Trained Bottlenecked Masked Autoencoders Are Better Dense Retrievers
Reciprocal Sequential Recommendation
Generative Next-Basket Recommendation
JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving
Improving Conversational Recommendation Systems via Counterfactual Data Simulation
Small Pre-trained Language Models Can be Fine-tuned as Large Models via Over-Parameterization
TOME: A Two-stage Approach for Model-based Retrieval
Zero-shot Visual Question Answering with Language Model Feedback
The Web Can Be Your Oyster for Improving Language Models
MVP: Multi-task Supervised Pre-training for Natural Language Generation
Learning to Imagine: Visually-Augmented Natural Language Generation
Diffusion Models for Non-autoregressive Text Generation: A Survey
EulerNet: Adaptive Feature Interaction Learning via Euler's Formula for CTR Prediction
Towards a More User-Friendly and Easy-to-Use Benchmark Library for Recommender Systems
Learning Vector-Quantized Item Representaction for Transferable Sequential Recommenders
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