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20222025
most citedTowards Fine-grained Causal Reasoning and QA

7 citations · 16 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CL20251 cited

Direct Value Optimization: Improving Chain-of-Thought Reasoning in LLMs with Refined Values

Hongbo Zhang, Han Cui, Guangsheng Bao +3

We introduce Direct Value Optimization (DVO), an innovative reinforcement learning framework for enhancing large language models in complex reasoning tasks. Unlike traditional meth…

cs.CL2024

A Rationale-centric Counterfactual Data Augmentation Method for Cross-Document Event Coreference Resolution

Bowen Ding, Qingkai Min, Shengkun Ma +3

Based on Pre-trained Language Models (PLMs), event coreference resolution (ECR) systems have demonstrated outstanding performance in clustering coreferential events across document…

cs.CL20221 cited

Pre-Training a Graph Recurrent Network for Language Representation

Yile Wang, Linyi Yang, Zhiyang Teng +2

Transformer-based pre-trained models have gained much advance in recent years, becoming one of the most important backbones in natural language processing. Recent work shows that t…

cs.CL20227 cited

Towards Fine-grained Causal Reasoning and QA

Linyi Yang, Zhen Wang, Yuxiang Wu +2

Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despi…

cs.CL20225 cited

Challenges for Open-domain Targeted Sentiment Analysis

Yun Luo, Hongjie Cai, Linyi Yang +3

Since previous studies on open-domain targeted sentiment analysis are limited in dataset domain variety and sentence level, we propose a novel dataset consisting of 6,013 human-lab…