arXiv AI

AutoDesign: Meta-Harness Optimization for Long-Horizon Agentic Design

arXiv:2608. 13560v1 Announce Type: cross Abstract: Transforming multimodal sources into condensed and structured media outputs can be fundamentally conceptualized as a long-horizon agentic process centered on a model-harness system.

arXiv AI

Jul 1

Human-Agent Collaborative Paper-to-Page Crafting

arXiv:2510. 19600v2 Announce Type: replace-cross Abstract: In the quest for scientific progress, communicating research is as vital as the discovery itself.

By Qianli Ma, Siyu Wang, Yilin Chen, Yinhao Tang, Yixiang Yang, Chang Guo, Bingjie Gao, Zhening Xing, Yanan Sun, Zhipeng Zhang

agents multimodal benchmarks safety

arXiv AI

5d ago

Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development

arXiv:2608. 13417v1 Announce Type: new Abstract: Autonomous agents are increasingly capable of improving models, systems, and other technical artifacts through long-horizon experimentation.

By Yiwei Li, Wanli Yang, Hexiang Tan, Xiangzhou Huang, Zhengyu Chen, Ziran Li, Borun Chen, Shanglin Lei, Huaisheng Zhu, Hao Tian, Fei Sun, Xunliang Cai, Jingang Wang

agents

arXiv AI

Jun 4

The Meta-Agent Challenge: Are Current Agents Capable of Autonomous Agent Development?

arXiv:2606. 04455v1 Announce Type: new Abstract: Current AI benchmarks evaluate agents on task execution within human-designed workflows.

By Xinyu Lu, Tianshu Wang, Pengbo Wang, zujie wen, Zhiqiang Zhang, Jun Zhou, Boxi Cao, Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun

agents benchmarks safety

arXiv AI

Jul 7

ResearchStudio-Reel: Automate the Last Mile of Research from Paper to Poster, Video, and Blog

arXiv:2607. 04438v1 Announce Type: cross Abstract: Research dissemination, turning a paper into a poster, a talk video, and a blog post, is still a manual last mile.

By Lingao Xiao, Yalun Dai, Yangyu Huang, Qihao Zhao, Wenshan Wu, Hugo He, Ruishuo Chen, Jin Jiang, Qianli Ma, Jiahuan Zhang, Xin Zhang, Ying Xin, Yang Ou, Yan Xia, Scarlett Li, Longbo Huang, Zhipeng Zhang, Yang He, Yap Kim Hui, Yan Lu

llms agents multimodal benchmarks

arXiv AI

6d ago

REVERE: Reflective Evolving Research Engineer

arXiv:2603. 20667v2 Announce Type: replace-cross Abstract: Existing prompt-optimization techniques rely on local signals, causing poor generalization across tasks.

By Balaji Dinesh Gangireddi, Aniketh Garikaparthi, Manasi Patwardhan, Arman Cohan

agents benchmarks

arXiv AI

Jun 4

AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?

arXiv:2606. 05080v1 Announce Type: new Abstract: Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, running experiments, measuring outcomes, and continuously refining artifacts.

By Zhangchen Xu, Junda Chen, Yue Huang, Dongfu Jiang, Jiefeng Chen, Hang Hua, Zijian Wu, Zheyuan Liu, Zexue He, Lichi Li, Shizhe Diao, Jiaxin Pei, Jinsung Yoon, Hao Zhang, Mengdi Wang, Radha Poovendran, Misha Sra, Alex Pentland, Zichen Chen

llms agents benchmarks

arXiv Machine Learning

Aug 5

Crayotter: Learning Long-Horizon Video Editing Agents via Group-Relative Preference Backpropagation

arXiv:2608. 02694v1 Announce Type: cross Abstract: Long-horizon video editing agents receive final-product feedback only after many interdependent decisions.

By Lecheng Yan, Jianze Lin, Yichong Zhang, Ben Pan, Wenxi Li, Chenyang Lyu, Liting Zhou, Cathal Gurrin

agents benchmarks

Hugging Face Trending Papers

Jul 5

ResearchStudio-Reel: Automate the Last Mile of Research from Paper to Poster, Video, and Blog

Research dissemination, turning a paper into a poster, a talk video, and a blog post, is still a manual last mile. Prior automation treats each artifact in isolation that each re-extract the paper from scratch, usually ship one-way renders the author cannot reopen in PowerPoint or Word, and gates quality on soft VLM-preference scores that plateau while load-bearing sections still read as empty.

llms agents multimodal benchmarks

arXiv AI

Jul 1

RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents

arXiv:2606. 22678v2 Announce Type: replace-cross Abstract: Agentic coding harnesses - such as Agent-Skills, Superpowers, and Agent-Rigor - are increasingly deployed to augment underlying LLMs for real-world software engineering tasks.

By Meher Bhaskar Madiraju, Meher Sai Preetam Madiraju

llms agents benchmarks

arXiv AI

Jul 13

Long-Horizon-Terminal-Bench: Testing the Limits of Agents on Long-Horizon Terminal Tasks with Dense Reward-Based Grading

arXiv:2607. 08964v1 Announce Type: new Abstract: AI agents have become capable of autonomously completing short, well-specified tasks.

By Zongxia Li, Zhongzhi Li, Yucheng Shi, Ruhan Wang, Junyao Yang, Zhichao Liu, Xiyang Wu, Anhao Li, Yue Yu, Ninghao Liu, Lichao Sun, Haotao Mi, LeoweiLiang

agents multimodal benchmarks

arXiv Machine Learning

Jun 2

ATLAS: Agentic Test-time Learning-to-Allocate Scaling

arXiv:2606. 01667v1 Announce Type: new Abstract: Test-time scaling has become a major way to improve large language model reasoning, but its orchestration has remained designer-engineered: a fixed sample budget, a fixed refinement loop, a fixed scoring rule, or a fixed search policy decides how compute is spent, leaving the model in charge of solving but not of orchestration.

By Peijia Qin, Qi Cao, Pengtao Xie

llms agents nlp multimodal benchmarks

Hugging Face Trending Papers

Jun 3

AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?

Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, running experiments, measuring outcomes, and continuously refining artifacts. Yet existing benchmarks for frontier models primarily evaluate either single-turn responses or short-horizon agent trajectories, failing to capture the challenges of sustained iterative improvement over extended time horizons.

llms agents benchmarks

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