https://github.com/ielab/dsr-poisoning
공식 코드Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks
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Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks
Dealing with Typos for BERT-based Passage Retrieval and Ranking
You can't pick your neighbors, or can you? When and how to rely on retrieval in the $k$NN-LM
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks
Large Language Model Augmented Narrative Driven Recommendations
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning
PK-Chat: Pointer Network Guided Knowledge Driven Generative Dialogue Model
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning
Improving Indonesian Text Classification Using Multilingual Language Model
An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM
Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM Interactions
IndexTTS: An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
Accessible Smart Contracts Verification: Synthesizing Formal Models with Tamed LLMs
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
Domain-Specific Language Model Post-Training for Indonesian Financial NLP
L-MAGIC: Language Model Assisted Generation of Images with Coherence
NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation
Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language
RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
Characterization of Large Language Model Development in the Datacenter
InternLM-Law: An Open Source Chinese Legal Large Language Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.