paper-with-me

Papers Review Generation

“Review Generation” 태그가 달린 논문 51편 · 필터 해제

AutoRev: Automatic Peer Review System for Academic Research Papers

2025-05-20 · Maitreya Prafulla Chitale, Ketaki Mangesh Shetye, Harshit Gupta, Manav Chaudhary 외

Generating a review for an academic research paper is a complex task that requires a deep understanding of the document's content and the interdependencies between its sections. It demands not only insight into technical…

Question AnsweringReview Generation

LLM-Based User Simulation for Low-Knowledge Shilling Attacks on Recommender Systems

2025-05-18 · Shengkang Gu, Jiahao Liu, Dongsheng Li, Guangping Zhang 외

Recommender systems (RS) are increasingly vulnerable to shilling attacks, where adversaries inject fake user profiles to manipulate system outputs. Traditional attack strategies often rely on simplistic heuristics, requi…

Language ModelingLanguage ModellingLarge Language ModelRecommendation Systems+2

Patience is all you need! An agentic system for performing scientific literature review

2025-03-28 · David Brett, Anniek Myatt

Large language models (LLMs) have grown in their usage to provide support for question answering across numerous disciplines. The models on their own have already shown promise for answering basic questions, however fail…

AllArticlesQuestion AnsweringRetrieval+1

Bridging Social Psychology and LLM Reasoning: Conflict-Aware Meta-Review Generation via Cognitive Alignment

2025-03-18 · Wei Chen, Han Ding, Meng Yuan, Zhao Zhang 외

The rapid growth of scholarly submissions has overwhelmed traditional peer review systems, driving the need for intelligent automation to preserve scientific rigor. While large language models (LLMs) show promise in auto…

Review Generation

Combining Large Language Models with Static Analyzers for Code Review Generation

2025-02-10 · Imen Jaoua, Oussama Ben Sghaier, Houari Sahraoui

Code review is a crucial but often complex, subjective, and time-consuming activity in software development. Over the past decades, significant efforts have been made to automate this process. Early approaches focused on…

RAGRetrieval-augmented GenerationReview Generation

Survey on Vision-Language-Action Models

2025-02-07 · Adilzhan Adilkhanov, Amir Yelenov, Assylkhan Seitzhanov, Ayan Mazhitov 외

This paper presents an AI-generated review of Vision-Language-Action (VLA) models, summarizing key methodologies, findings, and future directions. The content is produced using large language models (LLMs) and is intende…

Review GenerationSurveyVision-Language-Action

Leveraging Large Language Models for Comparative Literature Summarization with Reflective Incremental Mechanisms

2024-12-03 · Fernando Gabriela Garcia, Spencer Burns, Harrison Fuller

In this paper, we introduce ChatCite, a novel method leveraging large language models (LLMs) for generating comparative literature summaries. The ability to summarize research papers with a focus on key comparisons betwe…

Review Generation

Mixture of Knowledge Minigraph Agents for Literature Review Generation

2024-11-09 · Zhi Zhang, Yan Liu, Sheng-hua Zhong, Gong Chen 외

Literature reviews play a crucial role in scientific research for understanding the current state of research, identifying gaps, and guiding future studies on specific topics. However, the process of conducting a compreh…

Review Generation

Deep Transfer Learning Based Peer Review Aggregation and Meta-review Generation for Scientific Articles

2024-10-05 · Md. Tarek Hasan, Mohammad Nazmush Shamael, H. M. Mutasim Billah, Arifa Akter 외

Peer review is the quality assessment of a manuscript by one or more peer experts. Papers are submitted by the authors to scientific venues, and these papers must be reviewed by peers or other authors. The meta-reviewers…

ArticlesReview GenerationTransfer Learning

HiReview: Hierarchical Taxonomy-Driven Automatic Literature Review Generation

2024-10-02 · Yuntong Hu, Zhuofeng Li, Zheng Zhang, Chen Ling 외

In this work, we present HiReview, a novel framework for hierarchical taxonomy-driven automatic literature review generation. With the exponential growth of academic documents, manual literature reviews have become incre…

ClusteringReview Generation

MAPLE: Enhancing Review Generation with Multi-Aspect Prompt LEarning in Explainable Recommendation

2024-08-19 · Ching-Wen Yang, Che Wei Chen, Kun-da Wu, Hao Xu 외

Explainable Recommendation task is designed to receive a pair of user and item and output explanations to justify why an item is recommended to a user. Many models treat review-generation as a proxy of explainable recomm…

DiversityExplainable RecommendationHallucinationLanguage Modeling+5

Automated Review Generation Method Based on Large Language Models

2024-07-30 · Shican Wu, Xiao Ma, Dehui Luo, Lulu Li 외

Literature research, vital for scientific work, faces the challenge of surging information volumes exceeding researchers' processing capabilities. We present an automated review generation method based on large language …

ArticlesHallucinationReview Generation

Review-LLM: Harnessing Large Language Models for Personalized Review Generation

2024-07-10 · Qiyao Peng, Hongtao Liu, Hongyan Xu, Qing Yang 외

Product review generation is an important task in recommender systems, which could provide explanation and persuasiveness for the recommendation. Recently, Large Language Models (LLMs, e.g., ChatGPT) have shown superior …

PersuasivenessRecommendation SystemsReview Generation

Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions

2024-06-09 · Cheng Tan, Dongxin Lyu, Siyuan Li, Zhangyang Gao 외

Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields and have shown significant potential in the academic peer-review process. However, existing applications are primarily limite…

Review Generation

A Sentiment Consolidation Framework for Meta-Review Generation

2024-02-28 · Miao Li, Jey Han Lau, Eduard Hovy

Modern natural language generation systems with Large Language Models (LLMs) exhibit the capability to generate a plausible summary of multiple documents; however, it is uncertain if they truly possess the capability of …

Review GenerationText Generation

Reviewer2: Optimizing Review Generation Through Prompt Generation

2024-02-16 · Zhaolin Gao, Kianté Brantley, Thorsten Joachims

Recent developments in LLMs offer new opportunities for assisting authors in improving their work. In this paper, we envision a use case where authors can receive LLM-generated reviews that uncover weak points in the cur…

Review Generation

Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?

2024-01-18 · Marcio Fonseca, Shay B. Cohen

In this work, we investigate the controllability of large language models (LLMs) on scientific summarization tasks. We identify key stylistic and content coverage factors that characterize different types of summaries su…

Language ModelingLanguage ModellingLarge Language ModelReview Generation

MARG: Multi-Agent Review Generation for Scientific Papers

2024-01-08 · Mike D'Arcy, Tom Hope, Larry Birnbaum, Doug Downey

We study the ability of LLMs to generate feedback for scientific papers and develop MARG, a feedback generation approach using multiple LLM instances that engage in internal discussion. By distributing paper text across …

Review GenerationSpecificity

Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models

2023-12-24 · Ling Li, Shaohua Li, Winda Marantika, Alex C. Kot 외

Denoising Diffusion Probabilistic Model (DDPM) has shown great competence in image and audio generation tasks. However, there exist few attempts to employ DDPM in the text generation, especially review generation under r…

Audio GenerationDenoisingExplainable RecommendationRecommendation Systems+3

Privately Aligning Language Models with Reinforcement Learning

2023-10-25 · Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran 외

Positioned between pre-training and user deployment, aligning large language models (LLMs) through reinforcement learning (RL) has emerged as a prevailing strategy for training instruction following-models such as ChatGP…

Instruction FollowingPrivacy Preservingreinforcement-learningReinforcement Learning+2
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