1 citations · 3 across the 21 of their papers we have counts for
22 papers
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…
OneBar: An End-to-End Content-Grounded Generative Query Recommendation Framework for E-Commerce Video Feeds
Yao Tang, Ying Yang, Ben Chen +5
Short-video platforms now expose clickable search entries beneath the video player, enabling users to easily express content-induced search intent. However, conventional query reco…
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…
SVFSearch: A Multimodal Knowledge-Intensive Benchmark for Short-Video Frame Search in the Gaming Vertical Domain
Lingtao Mao, Huangyu Dai, Xinyu Sun +4
Multimodal large language models are increasingly used as agent backbones that understand multimodal inputs, plan retrieval actions, invoke external tools, and reason over retrieve…
TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval
Xinyu Sun, Huangyu Dai, Lingtao Mao +5
E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This image-to-multimodal retrieval se…
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…
UniDGF: A Unified Detection-to-Generation Framework for Hierarchical Object Visual Recognition
Xinyu Nan, Lingtao Mao, Huangyu Dai +8
Achieving visual semantic understanding requires a unified framework that simultaneously handles object detection, category prediction, and attribute recognition. However, current…
OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Ben Chen, Xian Guo, Siyuan Wang +25
Traditional e-commerce search systems employ multi-stage cascading architectures (MCA) that progressively filter items through recall, pre-ranking, and ranking stages. While effect…
COINS: SemantiC Ids Enhanced COLd Item RepresentatioN for Click-through Rate Prediction in E-commerce Search
Qihang Zhao, Zhongbo Sun, Xiaoyang Zheng +6
With the rise of modern search and recommendation platforms, insufficient collaborative information of cold-start items exacerbates the Matthew effect of existing platform items, c…
OneVision: An End-to-End Generative Framework for Multi-view E-commerce Vision Search
Zexin Zheng, Huangyu Dai, Lingtao Mao +8
Traditional vision search, similar to search and recommendation systems, follows the multi-stage cascading architecture (MCA) paradigm to balance efficiency and conversion. Specifi…
InfoGain-RAG: Boosting Retrieval-Augmented Generation via Document Information Gain-based Reranking and Filtering
Zihan Wang, Zihan Liang, Zhou Shao +7
Retrieval-Augmented Generation (RAG) has emerged as a promising approach to address key limitations of Large Language Models (LLMs), such as hallucination, outdated knowledge, and…
An LLM-LVLM Driven Agent for Iterative and Fine-Grained Image Editing
Zihan Liang, Jiahao Sun, Haoran Ma
Despite the remarkable capabilities of text-to-image (T2I) generation models, real-world applications often demand fine-grained, iterative image editing that existing methods strug…
H-PRM: A Pluggable Hotword Pre-Retrieval Module for Various Speech Recognition Systems
Huangyu Dai, Lingtao Mao, Ben Chen +5
Hotword customization is crucial in ASR to enhance the accuracy of domain-specific terms. It has been primarily driven by the advancements in traditional models and Audio large lan…
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…
MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning
Yufei Ma, Zihan Liang, Huangyu Dai +9
The growing demand for larger-scale models in the development of \textbf{L}arge \textbf{L}anguage \textbf{M}odels (LLMs) poses challenges for efficient training within limited comp…
Contrastive Token Learning with Similarity Decay for Repetition Suppression in Machine Translation
Huangyu Dai, Ben Chen, Kaidi Chen +3
For crosslingual conversation and trade, Neural Machine Translation (NMT) is pivotal yet faces persistent challenges with monotony and repetition in generated content. Traditional…
AssistSR: Task-oriented Video Segment Retrieval for Personal AI Assistant
Stan Weixian Lei, Difei Gao, Yuxuan Wang +4
It is still a pipe dream that personal AI assistants on the phone and AR glasses can assist our daily life in addressing our questions like ``how to adjust the date for this watch?…