# ResearchArcade: Graph Interface for Academic Tasks

arXiv: https://arxiv.org/abs/2511.22036 · HTML: https://mlsanity.com/paper/2511.22036/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 27 of its 31 references that are in the map.
- First posted on arXiv 27 Nov 2025.

## Builds on (most cited first, 27 of 27)

- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Qwen3 Technical Report](https://mlsanity.com/paper/2505.09388/) (2025)
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://mlsanity.com/paper/1911.05722/) (2019)
- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Improved Baselines with Visual Instruction Tuning](https://mlsanity.com/paper/2310.03744/) (2023)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [gpt-oss-120b & gpt-oss-20b Model Card](https://mlsanity.com/paper/2508.10925/) (2025)
- [Heterogeneous Graph Attention Network](https://mlsanity.com/paper/1903.07293/) (2019)
- [A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications](https://mlsanity.com/paper/1804.09635/) (2018)
- [SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs](https://mlsanity.com/paper/2308.03349/) (2023)
- [Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review](https://mlsanity.com/paper/2204.10805/) (2022)
- [ResearchTown: Simulator of Human Research Community](https://mlsanity.com/paper/2412.17767/) (2024)
- [DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models](https://mlsanity.com/paper/2406.11633/) (2024)
- [ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews](https://mlsanity.com/paper/2306.12587/) (2023)
- [How Far Are We From AGI: Are LLMs All We Need?](https://mlsanity.com/paper/2405.10313/) (2024)
- [unarXive 2022: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Network](https://mlsanity.com/paper/2303.14957/) (2023)
- [GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation](https://mlsanity.com/paper/2503.12600/) (2025)
- [Graph World Model](https://mlsanity.com/paper/2507.10539/) (2025)
- [OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining](https://mlsanity.com/paper/2402.15810/) (2024)
- [cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers](https://mlsanity.com/paper/2406.08398/) (2024)
- [ParaRev: Building a dataset for Scientific Paragraph Revision annotated with revision instruction](https://mlsanity.com/paper/2501.05222/) (2025)
- [Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized Academic Assistance](https://mlsanity.com/paper/2409.04593/) (2024)
- [TinyScientist: An Interactive, Extensible, and Controllable Framework for Building Research Agents](https://mlsanity.com/paper/2510.06579/) (2025)
- [MMCR: Benchmarking Cross-Source Reasoning in Scientific Papers](https://mlsanity.com/paper/2503.16856/) (2025)
- [Citation Recommendation for Research Papers via Knowledge Graphs](https://mlsanity.com/paper/2106.05633/) (2021)
- [GUIDE: Towards Scalable Advising for Research Ideas](https://mlsanity.com/paper/2507.08870/) (2025)

## Abstract (arXiv)

Academic research generates diverse data sources, and as researchers increasingly use machine learning to assist research tasks, a crucial question arises: Can we build a unified data interface to support the development of machine learning models for various academic tasks? Models trained on such a unified interface can better support human researchers throughout the research process, eventually accelerating knowledge discovery. In this work, we introduce ResearchArcade, a graph-based interface that connects multiple academic data sources, unifies task definitions, and supports a wide range of base models to address key academic challenges. ResearchArcade utilizes a coherent multi-table format with graph structures to organize data from different sources, including academic corpora from ArXiv and peer reviews from OpenReview, while capturing information with multiple modalities, such as text, figures, and tables. ResearchArcade also preserves temporal evolution at both the manuscript and community levels, supporting the study of paper revisions as well as broader research trends over time. Additionally, ResearchArcade unifies diverse academic task definitions and supports various models with distinct input requirements. Our experiments across six academic tasks demonstrate that combining cross-source and multi-modal information enables a broader range of tasks, while incorporating graph structures consistently improves performance over baseline methods. This highlights the effectiveness of ResearchArcade and its potential to advance research progress.