SOTAVerified

Information Retrieval

Information retrieval is the task of ranking a list of documents or search results in response to a query

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Papers

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Showing 2651–2700 of 4740 papers

TitleStatusHype
RDoC Task at BioNLP-OST 2019—0
RE-AdaptIR: Improving Information Retrieval through Reverse Engineered Adaptation—0
Reading and Thinking: Re-read LSTM Unit for Textual Entailment Recognition—0
Reading Protocol: Understanding what has been Read in Interactive Information Retrieval Tasks—0
Real-time information retrieval from Identity cards—0
Real-time Percussive Technique Recognition and Embedding Learning for the Acoustic Guitar—0
Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrieval—0
Real-world Conversational AI for Hotel Bookings—0
ReasoningRank: Teaching Student Models to Rank through Reasoning-Based Knowledge Distillation—0
Recall is the Proper Evaluation Metric for Word Segmentation—0
Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey—0
Recent Advances in Video Question Answering: A Review of Datasets and Methods—0
Recherche et extraction d'information dans des cas cliniques. Pr\'esentation de la campagne d'\'evaluation DEFT 2019 (Information Retrieval and Information Extraction from Clinical Cases)—0
Recognizing Chinese Judicial Named Entity using BiLSTM-CRF—0
Recognizing Descriptive Wikipedia Categories for Historical Figures—0
Recognizing Identical Events with Graph Kernels—0
Recognizing Insufficiently Supported Arguments in Argumentative Essays—0
Recognizing Reference Spans and Classifying their Discourse Facets—0
Recognizing Textual Entailment in Twitter Using Word Embeddings—0
Recognizing Textual Entailment Using Probabilistic Inference—0
Recommendation or Discrimination?: Quantifying Distribution Parity in Information Retrieval Systems—0
Recommender Systems Notation: Proposed Common Notation for Teaching and Research—0
Recommending Research Papers to Chemists: A Specialized Interface for Chemical Entity Exploration—0
Reconciling Methodological Paradigms: Employing Large Language Models as Novice Qualitative Research Assistants in Talent Management Research—0
Recourse for reclamation: Chatting with generative language models—0
Recovering Variable Names for Minified Code with Usage Contexts—0
Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors—0
Recurrent Neural Network Based Loanwords Identification in Uyghur—0
Recurrent Neural Network Encoder with Attention for Community Question Answering—0
Reddit Temporal N-gram Corpus and its Applications on Paraphrase and Semantic Similarity in Social Media using a Topic-based Latent Semantic Analysis—0
ReDecode Framework for Iterative Improvement in Paraphrase Generation—0
Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness—0
Redefining Information Retrieval of Structured Database via Large Language Models—0
Rediscovering ACL Discoveries Through the Lens of ACL Anthology Network Citing Sentences—0
Reducing Hallucinations in Language Model-based SPARQL Query Generation Using Post-Generation Memory Retrieval—0
Reducing Over-generation Errors for Automatic Keyphrase Extraction using Integer Linear Programming—0
Reducing Over-Weighting in Supervised Term Weighting for Sentiment Analysis—0
Reducing the climate impact of data portals: a case study—0
Reducing the Vision and Language Bias for Temporal Sentence Grounding—0
Refocusing on Relevance: Personalization in NLG—0
Reformulating Information Retrieval from Speech and Text as a Detection Problem—0
Regret Minimization in Stochastic Contextual Dueling Bandits—0
Regular expressions for decoding of neural network outputs—0
Regularized Autoencoders for Isometric Representation Learning—0
Regularized Interlingual Projections: Evaluation on Multilingual Transliteration—0
Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations—0
Reinforced Information Retrieval—0
Reinforcement Learning-driven Information Seeking: A Quantum Probabilistic Approach—0
Reinforcement Learning to Rank with Coarse-grained Labels—0
Reinforcement Speculative Decoding for Fast Ranking—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Two-tower Bi-Encoder (RoBERTa)Recall@10074.78—Unverified
2Siamese Bi-Encoder (RoBERTa)Recall@10071.63—Unverified
3BM25Recall@10051.33—Unverified
#ModelMetricClaimedVerifiedStatus
1RetroMAE v2MRR@1042.58—Unverified
2ConAE-256Time (ms)0.33—Unverified
3ConAE-128Time (ms)0.32—Unverified
#ModelMetricClaimedVerifiedStatus
1SGPT-BE-5.8BmAP@1000.16—Unverified
2TSDAEmAP@1000.15—Unverified
#ModelMetricClaimedVerifiedStatus
1hpipubcommoninfNDCG0.56—Unverified
2hpictallinfNDCG0.55—Unverified
#ModelMetricClaimedVerifiedStatus
1MINDHR@300.32—Unverified
#ModelMetricClaimedVerifiedStatus
1Distilled NetworknDCG@100.53—Unverified
#ModelMetricClaimedVerifiedStatus
1RetroMAEMRR@100.42—Unverified
#ModelMetricClaimedVerifiedStatus
1SGPT-5.8B-msmarconDCG@1050.25—Unverified
#ModelMetricClaimedVerifiedStatus
1Information Retrieval + SVM1:1 Accuracy83.79—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT+CONCEPT FILTERNDCG0.25—Unverified