https://github.com/iu-aes-ai4code/codequestionanswering
공식 코드Leveraging Large Language Models in Code Question Answering: Baselines and Issues
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Leveraging Large Language Models in Code Question Answering: Baselines and Issues
Shallow decision-making analysis in General Video Game Playing
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
Ensemble Semi-supervised Entity Alignment via Cycle-teaching
Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods
Localized Symbolic Knowledge Distillation for Visual Commonsense Models
Localized Symbolic Knowledge Distillation for Visual Commonsense Models
ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding
Inverse Kinematics for Neuro-Robotic Grasping with Humanoid Embodied Agents
Prompt-Based Monte-Carlo Tree Search for Goal-Oriented Dialogue Policy Planning
Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns
ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles
Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training
Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion
The Digitalization of Bioassays in the Open Research Knowledge Graph
DEER: Descriptive Knowledge Graph for Explaining Entity Relationships
K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressor
SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
AgentCF++: Memory-enhanced LLM-based Agents for Popularity-aware Cross-domain Recommendations
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation
Inductive Relation Prediction from Relational Paths and Context with Hierarchical Transformers
Collaborative Expert LLMs Guided Multi-Objective Molecular Optimization
ViLa-MIL: Dual-scale Vision-Language Multiple Instance Learning for Whole Slide Image Classification
CellTypeAgent: Trustworthy cell type annotation with Large Language Models
Item-side Fairness of Large Language Model-based Recommendation System
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.