Search Results for author:
Found 21 papers, 5 papers with code
Entity Relative Position Representation based Multi-head Selection for Joint Entity and Relation Extraction
Joint entity and relation extraction has received increasing interests recently, due to the capability of utilizing the interactions between both steps.
G4: Grounding-guided Goal-oriented Dialogues Generation with Multiple Documents
Goal-oriented dialogues generation grounded in multiple documents(MultiDoc2Dial) is a challenging and realistic task.
New Intent Discovery with Attracting and Dispersing Prototype
New Intent Discovery (NID) aims to recognize known and infer new intent categories with the help of limited labeled and large-scale unlabeled data.
MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL
Our framework comprises a core decomposer agent for Text-to-SQL generation with few-shot chain-of-thought reasoning, accompanied by two auxiliary agents that utilize external tools or models to acquire smaller sub-databases and refine erroneous SQL queries.
IEKM: A Model Incorporating External Keyword Matrices
In this paper, we propose an incorporation external keywords matrices model (IEKM) to address these challenges.
KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation
We propose Knowledgeable Prefix Tuning (KnowPrefix-Tuning), a two-stage tuning framework, bypassing the retrieval process in a knowledge-grounded conversation system by injecting prior knowledge into the lightweight knowledge prefix.
GripRank: Bridging the Gap between Retrieval and Generation via the Generative Knowledge Improved Passage Ranking
However, the retrieved passages are not ideal for guiding answer generation because of the discrepancy between retrieval and generation, i. e., the candidate passages are all treated equally during the retrieval procedure without considering their potential to generate a proper answer.
QURG: Question Rewriting Guided Context-Dependent Text-to-SQL Semantic Parsing
Context-dependent Text-to-SQL aims to translate multi-turn natural language questions into SQL queries.
CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parsers
Context-dependent text-to-SQL is the task of translating multi-turn questions into database-related SQL queries.
Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task Learning
In MLTC task, a document-label cross attention (CA) mechanism is adopted to generate a more discriminative document representation.
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation Extraction
Then, we propose to predict a subset of potential relations and filter out irrelevant ones to generate questions effectively.
Ranked #1 on
Relation Extraction
on ACE 2005
(Sentence Encoder metric)
Knowledge Based Machine Reading Comprehension
Machine reading comprehension (MRC) requires reasoning about both the knowledge involved in a document and knowledge about the world.
Keyphrase Generation with Correlation Constraints
In this paper, we study automatic keyphrase generation.
Learning to Collaborate for Question Answering and Asking
Secondly, directly applying GAN that regards all the generated questions as negative instances could not improve the accuracy of the QA model.
Table-to-Text: Describing Table Region with Natural Language
The model maps a row from a table to a continuous vector and then generates a natural language sentence by leveraging the semantics of a table.
Assertion-based QA with Question-Aware Open Information Extraction
We present assertion based question answering (ABQA), an open domain question answering task that takes a question and a passage as inputs, and outputs a semi-structured assertion consisting of a subject, a predicate and a list of arguments.
Content-Based Table Retrieval for Web Queries
Understanding the connections between unstructured text and semi-structured table is an important yet neglected problem in natural language processing.
Question Answering and Question Generation as Dual Tasks
On one side, the QA model judges whether the generated question of a QG model is relevant to the answer.
Constraint-Based Question Answering with Knowledge Graph
WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent knowledge-based question answering (KBQA) work.
