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Found 25 papers, 14 papers with code
Aligning Large Language Models to a Domain-specific Graph Database
Graph Databases (Graph DB) are widely applied in various fields, including finance, social networks, and medicine.
An LLM-Enhanced Adversarial Editing System for Lexical Simplification
Lexical Simplification (LS) aims to simplify text at the lexical level.
Unsupervised Text Style Transfer via LLMs and Attention Masking with Multi-way Interactions
Among existing methods for UTST tasks, attention masking approach and Large Language Models (LLMs) are deemed as two pioneering methods.
TreeEval: Benchmark-Free Evaluation of Large Language Models through Tree Planning
Recently, numerous new benchmarks have been established to evaluate the performance of large language models (LLMs) via either computing a holistic score or employing another LLM as a judge.
Safety of Multimodal Large Language Models on Images and Text
In this paper, we systematically survey current efforts on the evaluation, attack, and defense of MLLMs' safety on images and text.
Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trends
Natural Language Processing (NLP) aims to analyze text or speech via techniques in the computer science field.
MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models
The security concerns surrounding Large Language Models (LLMs) have been extensively explored, yet the safety of Multimodal Large Language Models (MLLMs) remains understudied.
Improving Zero-shot Visual Question Answering via Large Language Models with Reasoning Question Prompts
This results in a set of candidate answers.
R$^3$ Prompting: Review, Rephrase and Resolve for Chain-of-Thought Reasoning in Large Language Models under Noisy Context
More analyses and ablation studies show the robustness and generalization of R$^3$ prompting method in solving reasoning tasks in LLMs under noisy context.
Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation
Inspired by Chain-of-Thought (CoT) prompting, which is an in-context learning strategy for reasoning, we formulate KBQG task as a reasoning problem, where the generation of a complete question is splitted into a series of sub-question generation.
FlaCGEC: A Chinese Grammatical Error Correction Dataset with Fine-grained Linguistic Annotation
Chinese Grammatical Error Correction (CGEC) has been attracting growing attention from researchers recently.
History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling
Context information modeling is an important task in conversational KBQA.
Read, Diagnose and Chat: Towards Explainable and Interactive LLMs-Augmented Depression Detection in Social Media
This paper proposes a new depression detection system based on LLMs that is both interpretable and interactive.
Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
To address the calculation errors and improve the quality of generated reasoning steps, we extend PS prompting with more detailed instructions and derive PS+ prompting.
GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting
Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community.
Improving Compositional Generalization in Math Word Problem Solving
To improve the compositional generalization in MWP solving, we propose an iterative data augmentation method that includes diverse compositional variation into training data and could collaborate with MWP methods.
MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers
Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs.
Ranked #8 on
Math Word Problem Solving
on Math23K
Complex Knowledge Base Question Answering: A Survey
Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB).
Modeling Transitions of Focal Entities for Conversational Knowledge Base Question Answering
We propose a novel graph-based model to capture the transitions of focal entities and apply a graph neural network to derive a probability distribution of focal entities for each question, which is then combined with a standard KBQA module to perform answer ranking.
MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving
Math word problem (MWP) solving faces a dilemma in number representation learning.
Ranked #5 on
Math Word Problem Solving
on MathQA
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions
In this paper, we elaborately summarize the typical challenges and solutions for complex KBQA.
Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
In our approach, the student network aims to find the correct answer to the query, while the teacher network tries to learn intermediate supervision signals for improving the reasoning capacity of the student network.
Ranked #2 on
Semantic Parsing
on WebQuestionsSP
Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases
Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations.
Multi-level Head-wise Match and Aggregation in Transformer for Textual Sequence Matching
Transformer has been successfully applied to many natural language processing tasks.
Embedding WordNet Knowledge for Textual Entailment
In this paper, we study how we can improve a deep learning approach to textual entailment by incorporating lexical entailment relations from WordNet.
