activity
20232026
most citedYi: Open Foundation Models by 01.AI

47 citations · 105 across the 52 of their papers we have counts for

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Showing 2025Show all

27 papers · 1 filter

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.CL2025

DiscoX: Benchmarking Discourse-Level Translation task in Expert Domains

Xiying Zhao, Zhoufutu Wen, Zhixuan Chen +20

The evaluation of discourse-level translation in expert domains remains inadequate, despite its centrality to knowledge dissemination and cross-lingual scholarly communication. Whi…

cs.MM2025

AutoMV: An Automatic Multi-Agent System for Music Video Generation

Xiaoxuan Tang, Xinping Lei, Chaoran Zhu +10

Music-to-Video (M2V) generation for full-length songs faces significant challenges. Existing methods produce short, disjointed clips, failing to align visuals with musical structur…

cs.AI2025

RLoop: An Self-Improving Framework for Reinforcement Learning with Iterative Policy Initialization

Zeng Zhiyuan, Jiashuo Liu, Zhangyue Yin +3

While Reinforcement Learning for Verifiable Rewards (RLVR) is powerful for training large reasoning models, its training dynamics harbor a critical challenge: RL overfitting, where…

cs.LG2025★ 1 cited

Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation

Ziniu Li, Congliang Chen, Tianyun Yang +5

Large Language Models (LLMs) can self-improve through reinforcement learning, where they generate trajectories to explore and discover better solutions. However, this exploration p…

cs.CV2025

VideoScore2: Think before You Score in Generative Video Evaluation

Xuan He, Dongfu Jiang, Ping Nie +21

Recent advances in text-to-video generation have produced increasingly realistic and diverse content, yet evaluating such videos remains a fundamental challenge due to their multi-…

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

UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning

Haoming Wang, Haoyang Zou, Huatong Song +109

The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…

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.CL2025

Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions?

Qinyan Zhang, Xinping Lei, Ruijie Miao +18

Large Language Models (LLMs) achieve strong performance on diverse tasks but often exhibit cognitive inertia, struggling to follow instructions that conflict with the standardized…

cs.CL2025

WideSearch: Benchmarking Agentic Broad Info-Seeking

Ryan Wong, Jiawei Wang, Junjie Zhao +10

From professional research to everyday planning, many tasks are bottlenecked by wide-scale information seeking, which is more repetitive than cognitively complex. With the rapid de…

cs.AI2025

Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving

Luoxin Chen, Jinming Gu, Liankai Huang +33

LLMs have demonstrated strong mathematical reasoning abilities by leveraging reinforcement learning with long chain-of-thought, yet they continue to struggle with theorem proving d…

cs.CL2025

A Survey on Latent Reasoning

Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng +30

Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, especially when guided by explicit chain-of-thought (CoT) reasoning that verbalizes intermediate s…

cs.AI2025

First Return, Entropy-Eliciting Explore

Tianyu Zheng, Tianshun Xing, Qingshui Gu +10

Reinforcement Learning from Verifiable Rewards (RLVR) improves the reasoning abilities of Large Language Models (LLMs) but it struggles with unstable exploration. We propose FR3E (…

cs.CL2025

CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization

Zhongyuan Peng, Yifan Yao, Kaijing Ma +16

Translating natural language mathematical statements into formal, executable code is a fundamental challenge in automated theorem proving. While prior work has focused on generatio…

cs.CL2025

A Systematic Analysis of Hybrid Linear Attention

Dustin Wang, Rui-Jie Zhu, Steven Abreu +9

Transformers face quadratic complexity and memory issues with long sequences, prompting the adoption of linear attention mechanisms using fixed-size hidden states. However, linear…

cs.CL2025

SciDA: Scientific Dynamic Assessor of LLMs

Junting Zhou, Tingjia Miao, Yiyan Liao +15

Advancement in Large Language Models (LLMs) reasoning capabilities enables them to solve scientific problems with enhanced efficacy. Thereby, a high-quality benchmark for comprehen…

cs.CV2025

ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding

David Ma, Huaqing Yuan, Xingjian Wang +16

Although long-video understanding demands that models capture hierarchical temporal information -- from clip (seconds) and shot (tens of seconds) to event (minutes) and story (hour…

cs.CL2025

P2P: Automated Paper-to-Poster Generation and Fine-Grained Benchmark

Tao Sun, Enhao Pan, Zhengkai Yang +8

Academic posters are vital for scholarly communication, yet their manual creation is time-consuming. However, automated academic poster generation faces significant challenges in p…

cs.AI2025

FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models

Zhouliang Yu, Ruotian Peng, Keyi Ding +10

Formal mathematical reasoning remains a critical challenge for artificial intelligence, hindered by limitations of existing benchmarks in scope and scale. To address this, we prese…

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…

cs.CL2025★ 1 cited

Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning

ByteDance Seed, :, Jiaze Chen +267

We introduce Seed1.5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks. Seed1.5-Thinking achieves 8…

cs.CV2025

IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs

David Ma, Yuanxing Zhang, Jincheng Ren +17

Existing evaluation frameworks for Multimodal Large Language Models (MLLMs) primarily focus on image reasoning or general video understanding tasks, largely overlooking the signifi…

cs.CV2025

FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis

Luxi Chen, Zihan Zhou, Min Zhao +6

Generating flexible-view 3D scenes, including 360° rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel fr…