https://github.com/uuujf/TNAR
공식 코드Tangent-Normal Adversarial Regularization for Semi-supervised Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Information retrieval is the task of ranking a list of documents or search results in response to a query
<span style="color:grey; opacity: 0.6">( Image credit: sudhanshumittal )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Tangent-Normal Adversarial Regularization for Semi-supervised Learning
Unsupervised Submodular Rank Aggregation on Score-based Permutations
Extreme Compression of Large Language Models via Additive Quantization
A Survey on Recent Advances in Named Entity Recognition from Deep Learning models
NitiBench: A Comprehensive Studies of LLM Frameworks Capabilities for Thai Legal Question Answering
DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions
Expand, Rerank, and Retrieve: Query Reranking for Open-Domain Question Answering
One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support
The Effectiveness of Graph Contrastive Learning on Mathematical Information Retrieval
Text-to-SQL Generation for Question Answering on Electronic Medical Records
EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval
BERT is not The Count: Learning to Match Mathematical Statements with Proofs
TSPRank: Bridging Pairwise and Listwise Methods with a Bilinear Travelling Salesman Model
Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge Gaps
Clickbait Spoiling via Question Answering and Passage Retrieval
NaturalProofs: Mathematical Theorem Proving in Natural Language
Prompt Tuning on Graph-augmented Low-resource Text Classification
Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
The Effectiveness of Large Language Models in Transforming Unstructured Text to Standardized Formats
MES-RAG: Bringing Multi-modal, Entity-Storage, and Secure Enhancements to RAG
Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval
SciMMIR: Benchmarking Scientific Multi-modal Information Retrieval
Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding
Logical Consistency is Vital: Neural-Symbolic Information Retrieval for Negative-Constraint Queries
BM25S: Orders of magnitude faster lexical search via eager sparse scoring
Interactive Machine Comprehension with Information Seeking Agents
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.