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Found 23 papers, 10 papers with code
Towards a Holistic Evaluation of LLMs on Factual Knowledge Recall
By further decoupling model known and unknown knowledge, we find the degradation is attributed to exemplars that contradict a model's known knowledge, as well as the number of such exemplars.
Propagation and Pitfalls: Reasoning-based Assessment of Knowledge Editing through Counterfactual Tasks
Our analysis over the chain-of-thought generation of edited models further uncover key reasons behind the inadequacy of existing knowledge editing methods from a reasoning standpoint, involving aspects on fact-wise editing, fact recall ability, and coherence in generation.
UNITE: A Unified Benchmark for Text-to-SQL Evaluation
A practical text-to-SQL system should generalize well on a wide variety of natural language questions, unseen database schemas, and novel SQL query structures.
RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing
Reaction diagram parsing is the task of extracting reaction schemes from a diagram in the chemistry literature.
MolScribe: Robust Molecular Structure Recognition with Image-To-Graph Generation
Molecular structure recognition is the task of translating a molecular image into its graph structure.
Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization
Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objective.
Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources
C-CycleGAN transfers source samples at instance-level to an intermediate domain that is closer to the target domain with sentiment semantics preserved and without losing discriminative features.
Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
This paper explores the task of leveraging typology in the context of cross-lingual dependency parsing.
Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing
In this approach, a linear transformation is learned from contextual word alignments to align the contextualized embeddings independently trained in different languages.
GraphIE: A Graph-Based Framework for Information Extraction
Most modern Information Extraction (IE) systems are implemented as sequential taggers and only model local dependencies.
Multi-Source Domain Adaptation with Mixture of Experts
We propose a mixture-of-experts approach for unsupervised domain adaptation from multiple sources.
The HIT-SCIR System for End-to-End Parsing of Universal Dependencies
Our system includes three pipelined components: \textit{tokenization}, \textit{Part-of-Speech} (POS) \textit{tagging} and \textit{dependency parsing}.
A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks
Various treebanks have been released for dependency parsing.
A Unified Architecture for Semantic Role Labeling and Relation Classification
This paper describes a unified neural architecture for identifying and classifying multi-typed semantic relations between words in a sentence.
Chinese Grammatical Error Diagnosis with Long Short-Term Memory Networks
This paper introduces our Chinese Grammatical Error Diagnosis (CGED) system in the NLP-TEA-3 shared task for CGED.
A General Framework for Content-enhanced Network Representation Learning
This paper investigates the problem of network embedding, which aims at learning low-dimensional vector representation of nodes in networks.
Exploiting Multi-typed Treebanks for Parsing with Deep Multi-task Learning
Various treebanks have been released for dependency parsing.
Exploring Segment Representations for Neural Segmentation Models
Many natural language processing (NLP) tasks can be generalized into segmentation problem.
A Representation Learning Framework for Multi-Source Transfer Parsing
Cross-lingual model transfer has been a promising approach for inducing dependency parsers for low-resource languages where annotated treebanks are not available.
Cross-lingual zero-shot dependency parsing
Representation Learning
