most citedFutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction

1 citations · 2 across the 11 of their papers we have counts for

collaborators

11 papers

cs.AI2026

StartupBench: Benchmarking General-Purpose Agents on Market-Validated End-to-End Workflows

Liya Zhu, Xin Ma, Tao Liu +35

Recent advances in Large Language Models(LLMs) and agents have substantially improved the ability of AI systems to execute complex tasks. Yet existing benchmarks largely rely on re…

cs.CL2026

Civil Court Simulation with Large Language Models

Yifan Chen, Haitao Li, Kaiyuan Zhang +3

Court simulation bridges legal education and judicial practice, yet human-based simulations are costly and difficult to scale. Large language models (LLMs) offer a scalable alterna…

cs.CV2026

What-If World: A Causal Benchmark for General World Models in Embodied Scenarios

Kunlin Cai, Rui Song, Jinghuai Zhang +7

Video generation models are increasingly used as world simulators for tasks like driving and robotic manipulation. What matters in these settings is not whether a single video look…

cs.AI2026

Xpertbench: Expert Level Tasks with Rubrics-Based Evaluation

Xue Liu, Xin Ma, Yuxin Ma +36

As Large Language Models (LLMs) exhibit plateauing performance on conventional benchmarks, a pivotal challenge persists: evaluating their proficiency in complex, open-ended tasks c…

cs.AI2026

AutoVerifier: An Agentic Automated Verification Framework Using Large Language Models

Yuntao Du, Minh Dinh, Kaiyuan Zhang +1

Scientific and Technical Intelligence (S&TI) analysis requires verifying complex technical claims across rapidly growing literature, where existing approaches fail to bridge the ve…

cs.AI2026

FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains

Jiashuo Liu, Siyuan Chen, Zaiyuan Wang +38

Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, Futu…

cs.CL2025

MME-CC: A Challenging Multi-Modal Evaluation Benchmark of Cognitive Capacity

Kaiyuan Zhang, Chenghao Yang, Zhoufutu Wen +19

As reasoning models scale rapidly, the essential role of multimodality in human cognition has come into sharp relief, driving a growing need to probe vision-centric cognitive behav…

cs.LG2025

FinSearchComp: Towards a Realistic, Expert-Level Evaluation of Financial Search and Reasoning

Liang Hu, Jianpeng Jiao, Jiashuo Liu +20

Search has emerged as core infrastructure for LLM-based agents and is widely viewed as critical on the path toward more general intelligence. Finance is a particularly demanding pr…

cs.AI2025★ 1 cited

FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction

Zhiyuan Zeng, Jiashuo Liu, Siyuan Chen +28

Future prediction is a complex task for LLM agents, requiring a high level of analytical thinking, information gathering, contextual understanding, and decision-making under uncert…

cs.CV2025★ 1 cited

Seed1.5-VL Technical Report

Dong Guo, Faming Wu, Feida Zhu +194

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…

cs.CL2025

MARS-Bench: A Multi-turn Athletic Real-world Scenario Benchmark for Dialogue Evaluation

Chenghao Yang, Yinbo Luo, Zhoufutu Wen +8

Large Language Models (\textbf{LLMs}), e.g. ChatGPT, have been widely adopted in real-world dialogue applications. However, LLMs' robustness, especially in handling long complex di…