SOTAVerified

Intent Recognition

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 93 papers

TitleStatusHype
Training Compute-Optimal Large Language ModelsCode6
MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in ConversationsCode2
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
New Intent Discovery with Pre-training and Contrastive LearningCode1
Understanding and Enhancing the Transferability of Jailbreaking AttacksCode1
Cache me if you Can: an Online Cost-aware Teacher-Student framework to Reduce the Calls to Large Language ModelsCode1
MIntRec: A New Dataset for Multimodal Intent RecognitionCode1
LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-ExplanationsCode1
Continual Learning in Task-Oriented Dialogue SystemsCode1
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent DetectionCode1
Large Language Models for Power Scheduling: A User-Centric ApproachCode1
Token-Level Contrastive Learning with Modality-Aware Prompting for Multimodal Intent RecognitionCode1
Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture—0
A k-Nearest Neighbor Approach towards Multi-level Sequence Labeling—0
Avaya Conversational Intelligence: A Real-Time System for Spoken Language Understanding in Human-Human Call Center Conversations—0
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
WDMIR: Wavelet-Driven Multimodal Intent Recognition—0
Data Augmentation with Paraphrase Generation and Entity Extraction for Multimodal Dialogue System—0
ADMC: Attention-based Diffusion Model for Missing Modalities Feature Completion—0
Contextual Augmented Global Contrast for Multimodal Intent Recognition—0
Conformal Intent Classification and Clarification for Fast and Accurate Intent Recognition—0
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection—0
Conversational Intent Understanding for Passengers in Autonomous Vehicles—0
Automated hypothesis generation via Evolutionary Abduction—0
Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy 92.8—Unverified
2Gopher-280B (few-shot, k=5)Accuracy 88.7—Unverified