1 citations · 1 across the 11 of their papers we have counts for
12 papers
Dr. Free: You Don't Need Difficulty Rewards for Self-Evolving Search Agents
Zhipeng Qian, Zihan Liang, Yufei Ma +10
A central limitation of current data-free self-evolution methods for training search agents is their reliance on difficulty-based proposer rewards. These methods reward a proposer…
OneRetrieval: Unifying Multi-Branch E-commerce Retrieval with an Editable Generative Model
Xuxin Zhang, Ben Chen, Yue Lv +13
Industrial e-commerce search serves hundreds of millions of items through a multi-branch retrieval stage fused by hand-tuned merging without joint optimization. Generative retrieva…
Plan Before Search: Search Agents Need Plan
Zhipeng Qian, Zihan Liang, Yufei Ma +7
Training large language models as retrieval-augmented reasoning agents typically combines reinforcement learning with an SFT cold start distilled from a stronger model. However, th…
Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning
Zihan Liang, Yufei Ma, Ben Chen +4
Post-training has become the dominant recipe for turning a language model into a competent search-augmented reasoning agent. A line of recent work pushes its performance further by…
SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning
Yufei Ma, Zihan Liang, Ben Chen +6
Search-augmented reasoning agents interleave internal reasoning with calls to an external retriever, and their performance relies on the quality of each issued query. However, unde…
Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations
Bochao Liu, Zhipeng Qian, Yang Zhao +10
Operating and maintaining (O&M) large-scale online engine systems (eg, search, recommendation and advertising) demands substantial human effort for release monitoring, alert respon…
IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning
Zihan Liang, Yufei Ma, Ben Chen +6
Reinforcement learning has emerged as an effective paradigm for training large language models to perform search-augmented reasoning. However, existing approaches rely on trajector…
OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework
Ben Chen, Siyuan Wang, Yufei Ma +20
Generative Retrieval (GR) has emerged as a promising paradigm for modern search systems. Compared to multi-stage cascaded architecture, it offers advantages such as end-to-end join…
CSMCIR: CoT-Enhanced Symmetric Alignment with Memory Bank for Composed Image Retrieval
Zhipeng Qian, Zihan Liang, Yufei Ma +7
Composed Image Retrieval (CIR) enables users to search for target images using both a reference image and manipulation text, offering substantial advantages over single-modality re…
UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion
Zihan Liang, Yufei Ma, ZhiPeng Qian +6
Current e-commerce multimodal retrieval systems face two key limitations: they optimize for specific tasks with fixed modality pairings, and lack comprehensive benchmarks for evalu…
Multi-branch Collaborative Learning Network for 3D Visual Grounding
Zhipeng Qian, Yiwei Ma, Zhekai Lin +4
3D referring expression comprehension (3DREC) and segmentation (3DRES) have overlapping objectives, indicating their potential for collaboration. However, existing collaborative ap…
AnyTrans: Translate AnyText in the Image with Large Scale Models
Zhipeng Qian, Pei Zhang, Baosong Yang +5
This paper introduces AnyTrans, an all-encompassing framework for the task-Translate AnyText in the Image (TATI), which includes multilingual text translation and text fusion withi…