paper-with-me

Papers Paper generation

“Paper generation” 태그가 달린 논문 20편 · 필터 해제

Spark-to-Paper: End-to-End Research Paper Generation as a Composable Skill

2026-08-12 · Zhuoyang Qian, Biao Wu, Yiran Wang, Chris D Yan 외 hf

Turning a research idea into a complete paper requires more than text generation: the system must retrieve literature, design and execute experiments, revise claims according to evidence, produce publication-ready figure…

Paper generationText Generation

OpenCLAW-P2P v7.0-P2PCLAW: Resilient Multi-Layer Persistence, Live Reference Verification, and Production-Scale Evaluation of Decentralized AI Peer Review v7.0 -- Mathematical Corrections & Ecosystem Developments Edition

2026-04-06 · Francisco Angulo de Lafuente, Teerth Sharma, Vladimir Veselov, Seid Mohammed Abdu 외 arxiv

This paper presents OpenCLAW-P2P v7.0, a comprehensive evolution of the decentralized collective-intelligence platform in which autonomous AI agents publish, peer-review, score, and iteratively improve scientific researc…

Paper generation

OUTLINEFORGE: Hierarchical Reinforcement Learning with Explicit States for Scientific Writing

2026-01-14 · Yilin Bao, Ziyao He, Zayden Yang arxiv

Scientific paper generation requires document-level planning and factual grounding, but current large language models, despite their strong local fluency, often fail in global structure, input coverage, and citation cons…

Hierarchical Reinforcement LearningPaper generation

ARISE: Agentic Rubric-Guided Iterative Survey Engine for Automated Scholarly Paper Generation

2025-11-21 · Zi Wang, Xingqiao Wang, Sangah Lee, Xiaowei Xu arxiv

The rapid expansion of scholarly literature presents significant challenges in synthesizing comprehensive, high-quality academic surveys. Recent advancements in agentic systems offer considerable promise for automating t…

Paper generation

A Survey of AI Scientists

2025-10-27 · Guiyao Tie, Pan Zhou, Lichao Sun arxiv

Artificial intelligence is undergoing a profound transition from a computational instrument to an autonomous originator of scientific knowledge. This emerging paradigm, the AI scientist, is architected to emulate the com…

Paper generation

BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers?

2025-10-20 · Fengqing Jiang, Yichen Feng, Yuetai Li, Luyao Niu 외 arxiv

The convergence of LLM-powered research assistants and AI-based peer review systems creates a critical vulnerability: fully automated publication loops where AI-generated research is evaluated by AI reviewers without hum…

Paper generation

SurveyG: A Multi-Agent LLM Framework with Hierarchical Citation Graph for Automated Survey Generation

2025-10-09 · Minh-Anh Nguye, Minh-Duc Nguyen, Ha Lan N. T., Kieu Hai Dang 외 arxiv

Large language models (LLMs) are increasingly adopted for automating survey paper generation \cite{wang2406autosurvey, liang2025surveyx, yan2025surveyforge,su2025benchmarking,wen2025interactivesurvey}. Existing approache…

Paper generation

FRAME: Feedback-Refined Agent Methodology for Enhancing Medical Research Insights

2025-05-06 · Chengzhang Yu, Yiming Zhang, Zhixin Liu, Zenghui Ding 외

The automation of scientific research through large language models (LLMs) presents significant opportunities but faces critical challenges in knowledge synthesis and quality assurance. We introduce Feedback-Refined Agen…

Paper generation

InteractiveSurvey: An LLM-based Personalized and Interactive Survey Paper Generation System

2025-03-31 · Zhiyuan Wen, Jiannong Cao, Zian Wang, Beichen Guo 외

The exponential growth of academic literature creates urgent demands for comprehensive survey papers, yet manual writing remains time-consuming and labor-intensive. Recent advances in large language models (LLMs) and ret…

Paper generationRAGRetrievalRetrieval-augmented Generation+1

Vietnamese Poem Generation & The Prospect Of Cross-Language Poem-To-Poem Translation

2024-01-02 · Triet Minh Huynh, Quan Le Bao

Poetry generation has been a challenging task in the field of Natural Language Processing, as it requires the model to understand the nuances of language, sentiment, and style. In this paper, we propose using Large Langu…

Paper generation

Reinforcement Learning Guided Multi-Objective Exam Paper Generation

2023-03-02 · Yuhu Shang, Xuexiong Luo, Lihong Wang, Hao Peng 외

To reduce the repetitive and complex work of instructors, exam paper generation (EPG) technique has become a salient topic in the intelligent education field, which targets at generating high-quality exam paper automatic…

Knowledge TracingPaper generationreinforcement-learningReinforcement Learning+1

An Empirical Study of Finding Similar Exercises

2021-11-16 · Tongwen Huang, Xihua Li

Education artificial intelligence aims to profit tasks in the education domain such as intelligent test paper generation and consolidation exercises where the main technique behind is how to match the exercises, known as…

DiversityLanguage ModelingLanguage ModellingPaper generation

TUDA-Reproducibility @ ReproGen: Replicability of Human Evaluation of Text-to-Text and Concept-to-Text Generation

2021-08-01 · INLG (ACL) 2021 8 · Christian Richter, Yanran Chen, Steffen Eger

This paper describes our contribution to the Shared Task ReproGen by Belz et al. (2021), which investigates the reproducibility of human evaluations in the context of Natural Language Generation. We selected the paper “G…

Concept-To-Text GenerationPaper generationText Generation

Optimize the Co-expansion of Generation and Transmission Considering Wind Power in the US Eastern Interconnection

2021-01-11 · Shutang You

This paper studies the generation and transmission expansion co-optimization problem with a high wind power penetration rate in large-scale power grids. In this paper, generation and transmission expansion co-optimizatio…

Paper generation

Gamification Platform for Collecting Task-oriented Dialogue Data

2020-05-01 · LREC 2020 5 · Haruna Ogawa, Hitoshi Nishikawa, Takenobu Tokunaga, Hikaru Yokono

Demand for massive language resources is increasing as the data-driven approach has established a leading position in Natural Language Processing. However, creating dialogue corpora is still a difficult task due to the c…

DiversityPaper generation

Neural Academic Paper Generation

2019-12-02 · Samet Demir, Uras Mutlu, Özgur Özdemir

In this work, we tackle the problem of structured text generation, specifically academic paper generation in $\LaTeX{}$, inspired by the surprisingly good results of basic character-level language models. Our motivation …

Language ModelingLanguage ModellingPaper generationText Generation

PaperRobot: Incremental Draft Generation of Scientific Ideas

2019-05-20 · ACL 2019 7 · Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight 외

We present a PaperRobot who performs as an automatic research assistant by (1) conducting deep understanding of a large collection of human-written papers in a target domain and constructing comprehensive background know…

Graph AttentionKnowledge GraphsPaper generationPaper generation (abstract-to-conclusion)+3

Identifying Computer-Translated Paragraphs using Coherence Features

2018-12-28 · PACLIC 2018 12 · Hoang-Quoc Nguyen-Son, Ngoc-Dung T. Tieu, Huy H. Nguyen, Junichi Yamagishi 외

We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences. We conducted an experiment with a parallel German corpus containing 2000 human-created and 200…

Paper generationTranslation

Paper Abstract Writing through Editing Mechanism

2018-05-15 · ACL 2018 7 · Qingyun Wang, Zhi-Hao Zhou, Lifu Huang, Spencer Whitehead 외

We present a paper abstract writing system based on an attentive neural sequence-to-sequence model that can take a title as input and automatically generate an abstract. We design a novel Writing-editing Network that can…

Paper generationText Generation

WSNet: Learning Compact and Efficient Networks with Weight Sampling

2018-01-01 · ICLR 2018 1 · Xiaojie Jin, Yingzhen Yang, Ning Xu, Jianchao Yang 외

We present a new approach and a novel architecture, termed WSNet, for learning compact and efficient deep neural networks. Existing approaches conventionally learn full model parameters independently and then compress t…

Audio ClassificationGeneral ClassificationPaper generationQuantization
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