https://github.com/haodeqi/BenchmarkingIntentDetection
공식 코드Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations
Papers with Code 아카이브
Intent Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Intent Detection is a task of determining the underlying purpose or goal behind a user's search query given a context. The task plays a significant role in search and recommendations. A traditional approach for intent detection implies using an intent detector model to classify user search query into predefined intent categories, given a context. One of the key challenges of the task implies identifying user intents for cold-start sessions, i.e., search sessions initiated by a non-logged-in or unrecognized user.
Source: Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers <span class="description-source">
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/haohao11/MCENET
공식 코드MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic
https://github.com/hdzhang-code/dftplus
공식 코드Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training
https://github.com/hellohaptik/HINT3
공식 코드https://github.com/hqsiswiliam/punctuation-restoration-scl
공식 코드Token-Level Supervised Contrastive Learning for Punctuation Restoration
https://github.com/huawei-noah/noah-research
공식 코드Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection
https://github.com/idiap/slu_representations
공식 코드https://github.com/jasonwu0731/ToD-BERT
공식 코드TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue
https://github.com/jdcomsearch/jdsearch-22
공식 코드Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search
https://github.com/jiangshdd/learningtoselect
공식 코드https://github.com/jianguoz/Few-Shot-Intent-Detection
공식 코드https://github.com/jiezouir/pscon
공식 코드https://github.com/joeying1019/sdif-da
공식 코드https://github.com/kangbrilliant/DCA-Net
공식 코드A Co-Interactive Transformer for Joint Slot Filling and Intent Detection
https://github.com/karansikka1/documentIntent_emnlp19
공식 코드Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts
https://github.com/looperxx/proslu
공식 코드Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding
https://github.com/mainlp/auxtasks-bavarian-sid
공식 코드https://github.com/mainlp/norsid
공식 코드https://github.com/moore3930/SlotRefine
공식 코드SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling
https://github.com/mrzhengxin/multi_intent_2022
공식 코드DialogUSR: Complex Dialogue Utterance Splitting and Reformulation for Multiple Intent Detection
https://github.com/mushfiqur11/bangla-sylheti-snips
공식 코드Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti
https://github.com/nhhoang96/Semantic_Matching
공식 코드Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
https://github.com/nhhoang96/multicl_slot_induction
공식 코드Slot Induction via Pre-trained Language Model Probing and Multi-level Contrastive Learning
https://github.com/nicolas-lair/AidMe
공식 코드User-in-the-loop Adaptive Intent Detection for Instructable Digital Assistant
https://github.com/observeai-research/nli-fsl
공식 코드Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection
https://github.com/octaviaguo/chattychef
공식 코드Improved Instruction Ordering in Recipe-Grounded Conversation
https://github.com/peijiez/intentrec4maps
공식 코드Intention Recognition in Real-Time Interactive Navigation Maps
https://github.com/pgurunath/confusion2vec_2.0
공식 코드Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with Subwords
https://github.com/pgurunath/slu_confusion2vec
공식 코드https://github.com/prakharguptaz/Instructdial
공식 코드InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
https://github.com/rafiepour/CTran
공식 코드CTRAN: CNN-Transformer-based Network for Natural Language Understanding
https://github.com/salesforce/DNNC-few-shot-intent
공식 코드Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
https://github.com/salesforce/fewshot_absa
공식 코드A Generative Language Model for Few-shot Aspect-Based Sentiment Analysis
https://github.com/smileix/cpp
공식 코드https://github.com/stoyian/OCaTS
공식 코드https://github.com/sukannyapurkayastha/mnid
공식 코드A Framework to Generate High-Quality Datapoints for Multiple Novel Intent Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.