SOTAVerified

Chunking

Chunking, also known as shallow parsing, identifies continuous spans of tokens that form syntactic units such as noun phrases or verb phrases.

Example:

| Vinken | , | 61 | years | old | | --- | ---| --- | --- | --- | | B-NLP| I-NP | I-NP | I-NP | I-NP |

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 447 papers

TitleStatusHype
CLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs—0
A Unified Framework for Structured Prediction: From Theory to Practice—0
ClearTK-TimeML: A minimalist approach to TempEval 2013—0
ClearTK 2.0: Design Patterns for Machine Learning in UIMA—0
A Unified Framework for Discourse Argument Identification via Shallow Semantic Parsing—0
An Algebra for Feature Extraction—0
Action abstractions for amortized sampling—0
Chunk Twice, Embed Once: A Systematic Study of Segmentation and Representation Trade-offs in Chemistry-Aware Retrieval-Augmented Generation—0
ChunkRAG: Novel LLM-Chunk Filtering Method for RAG Systems—0
Chunking the Critic: A Transformer-based Soft Actor-Critic with N-Step Returns—0
Hierarchical Working Memory and a New Magic Number—0
Attending to Characters in Neural Sequence Labeling Models—0
A Model of Vietnamese Person Named Entity Question Answering System—0
Hierarchical Recurrent Neural Network for Document Modeling—0
HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation—0
Chunking Clinical Text Containing Non-Canonical Language—0
Habits of Mind: Reusing Action Sequences for Efficient Planning—0
Grounding Language Model with Chunking-Free In-Context Retrieval—0
Chunker diff\'erents types de discours oraux : d\'efis pour l'apprentissage automatique (Chunking different spoken speech types : challenges for machine learning)—0
Chunked Lists versus Extensible Arrays for Text Inversion—0
A CRF Method of Identifying Prepositional Phrases in Chinese Patent Texts—0
Accelerating Vision-Language-Action Model Integrated with Action Chunking via Parallel Decoding—0
A Boosted Semi-Markov Perceptron—0
Graph- and surface-level sentence chunking—0
CHORUS: Zero-shot Hierarchical Retrieval and Orchestration for Generating Linear Programming Code—0
At a Glance: The Impact of Gaze Aggregation Views on Syntactic Tagging—0
From Imitation to Refinement -- Residual RL for Precise Assembly—0
From Dionysius Emerges Apollo -- Learning Patterns and Abstractions from Perceptual Sequences—0
Chinese Descriptive and Resultative V-de Constructions. A Dependency-based Analysis—0
A Survey on Recent Advances in Sequence Labeling from Deep Learning Models—0
Forgetting Exceptions is Harmful in Language Learning—0
CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation—0
Fine-tuned vs. Prompt-tuned Supervised Representations: Which Better Account for Brain Language Representations?—0
From Finite-State to Inversion Transductions: Toward Unsupervised Bilingual Grammar Induction—0
Feature-Frequency--Adaptive On-line Training for Fast and Accurate Natural Language Processing—0
CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System—0
A Sequential Neural Encoder with Latent Structured Description for Modeling Sentences—0
Generalization of metric classification algorithms for sequences classification and labelling—0
A Cost Sensitive Part-of-Speech Tagging: Differentiating Serious Errors from Minor Errors—0
Feature-based Neural Language Model and Chinese Word Segmentation—0
Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection—0
GuiTAR-based Pronominal Anaphora Resolution in Bengali—0
Capturing Long-distance Dependencies in Sequence Models: A Case Study of Chinese Part-of-speech Tagging—0
Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling—0
Caption Generation of Robot Behaviors based on Unsupervised Learning of Action Segments—0
Hidden Markov tree models for semantic class induction—0
Artificially Evolved Chunks for Morphosyntactic Analysis—0
Hierarchical Word Structure-based Parsing: A Feasibility Study on UD-style Dependency Parsing in Japanese—0
Factorial Hidden Markov Models for Learning Representations of Natural Language—0
Exploring RWKV for Memory Efficient and Low Latency Streaming ASR—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACEExact Span F197.3—Unverified
2BERT-CRF (Replicated in AdaSeq)Exact Span F197.18—Unverified
3ELMo + MAT + Multi-TaskExact Span F197.04—Unverified
4CVT+Multi-Task+LargeExact Span F196.98—Unverified
5ELMo + Multi-TaskExact Span F196.83—Unverified
6FlairExact Span F196.72—Unverified
7SeqVATExact Span F195.45—Unverified
8Adversarial TrainingExact Span F195.25—Unverified
9BiLSTM-CRFExact Span F195.18—Unverified
#ModelMetricClaimedVerifiedStatus
1ACEF1 score97.3—Unverified
2Flair embeddingsF1 score96.72—Unverified
3JMTF1 score95.77—Unverified
4Low supervisionF1 score95.57—Unverified
5IntNet + BiLSTM-CRFF1 score95.29—Unverified
6Suzuki and IsozakiF1 score95.15—Unverified
7NCRF++F1 score95.06—Unverified
8BI-LSTM-CRF (Senna) (ours)F1 score94.46—Unverified
#ModelMetricClaimedVerifiedStatus
1ACEF195—Unverified
2Wang et al., 2020F194.4—Unverified
3AINF194.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Wang et al., 2020F192—Unverified
2AINF191.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Def2VecAUC93.07—Unverified