activity
20232025
most citedAgent models: Internalizing Chain-of-Action Generation into Reasoning models

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2025

SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understanding

Yuqi Yang, Weiqi Wang, Baixuan Xu +13

Session history is a common way of recording user interacting behaviors throughout a browsing activity with multiple products. For example, if an user clicks a product webpage and…

cs.CL2025

ExpertLongBench: Benchmarking Language Models on Expert-Level Long-Form Generation Tasks with Structured Checklists

Jie Ruan, Inderjeet Nair, Shuyang Cao +14

This paper introduces ExpertLongBench, an expert-level benchmark containing 11 tasks from 9 domains that reflect realistic expert workflows and applications. Beyond question answer…

cs.AI2025★ 1 cited

Agent models: Internalizing Chain-of-Action Generation into Reasoning models

Yuxiang Zhang, Yuqi Yang, Jiangming Shu +2

Traditional agentic workflows rely on external prompts to manage interactions with tools and the environment, which limits the autonomy of reasoning models. We position \emph{Large…

cs.AI2024

OpenRFT: Adapting Reasoning Foundation Model for Domain-specific Tasks with Reinforcement Fine-Tuning

Yuxiang Zhang, Yuqi Yang, Jiangming Shu +3

OpenAI's recent introduction of Reinforcement Fine-Tuning (RFT) showcases the potential of reasoning foundation model and offers a new paradigm for fine-tuning beyond simple patter…

cs.SE2024

o1-Coder: an o1 Replication for Coding

Yuxiang Zhang, Shangxi Wu, Yuqi Yang +4

The technical report introduces O1-CODER, an attempt to replicate OpenAI's o1 model with a focus on coding tasks. It integrates reinforcement learning (RL) and Monte Carlo Tree Sea…

cs.AI2024

Exploring the Privacy Protection Capabilities of Chinese Large Language Models

Yuqi Yang, Xiaowen Huang, Jitao Sang

Large language models (LLMs), renowned for their impressive capabilities in various tasks, have significantly advanced artificial intelligence. Yet, these advancements have raised…

cs.LG2023★ 1 cited

Meta-DM: Applications of Diffusion Models on Few-Shot Learning

Wentao Hu, Xiurong Jiang, Jiarun Liu +2

In the field of few-shot learning (FSL), extensive research has focused on improving network structures and training strategies. However, the role of data processing modules has no…