9 citations · 21 across the 20 of their papers we have counts for
21 papers
Neos: Learning to Interleave Search and Visual Reasoning
Ekko He, Jack Hong, Shilin Yan +8
Recent multimodal deep search agents have advanced tool use and visual content retrieval, yet they still struggle to convert intermediate visual evidence into actionable guidance f…
AdaVDR: Adaptive Tool Use and Reflection for Video Deep Research
Xintong Zhang, Xiaomeng Fan, Shilin Yan +7
Video deep research aims to answer questions by jointly understanding video content and retrieving external knowledge from the open Web. However, these tasks often require diverse…
Business Arena: Benchmarking LLM Agents in a Realistic Marketplace
Yijun Pan, Yukun Lian, Kunyu Shi +5
Running a business is a challenging form of intelligent work. Operators must infer opportunities from partial signals, commit capital under uncertainty, adapt to delayed outcomes i…
TouchAnything: A Dataset and Framework for Bimanual Tactile Estimation from Egocentric Video
Jianyi Zhou, Ziteng Gao, Feiyang Hong +11
Egocentric human video data, which captures rich human-environment interactions and can be collected at scale, has become a key driver of embodied intelligence research. However, e…
Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models
Shilin Yan, Jintao Tong, Hongwei Xue +6
The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a profound meta-cognitive deficit…
MM-CondChain: A Programmatically Verified Benchmark for Visually Grounded Deep Compositional Reasoning
Haozhan Shen, Shilin Yan, Hongwei Xue +5
Multimodal Large Language Models (MLLMs) are increasingly used to carry out visual workflows such as navigating GUIs, where the next step depends on verified visual compositional c…
SwimBird: Eliciting Switchable Reasoning Mode in Hybrid Autoregressive MLLMs
Jintao Tong, Shilin Yan, Hongwei Xue +5
Multimodal Large Language Models (MLLMs) have made remarkable progress in multimodal perception and reasoning by bridging vision and language. However, most existing MLLMs perform…
JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks
Lanbo Lin, Jiayao Liu, Tianyuan Yang +5
Evaluating agentic AI on open-ended professional tasks faces a fundamental dilemma between rigor and flexibility. Static rubrics provide rigorous, reproducible assessment but fail…
Hybrid Reward Normalization for Process-supervised Non-verifiable Agentic Tasks
Peiran Xu, Zhuohao Li, Xiaoying Xing +3
Large Language Models (LLMs) increasingly rely on external tools such as search engines to solve complex agentic tasks that require reasoning and external knowledge retrieval. Rece…
Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation
Jianxing Ma, Zhibo Xiao, Luwei Yang +5
To cater to users' desire for an immersive browsing experience, numerous e-commerce platforms provide various recommendation scenarios, with a focus on Trigger-Induced Recommendati…
SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation
Kaiming Shen, Xichen Ding, Zixiang Zheng +4
The modeling of users' behaviors is crucial in modern recommendation systems. A lot of research focuses on modeling users' lifelong sequences, which can be extremely long and somet…
Towards Efficient Replay in Federated Incremental Learning
Yichen Li, Qunwei Li, Haozhao Wang +3
In Federated Learning (FL), the data in each client is typically assumed fixed or static. However, data often comes in an incremental manner in real-world applications, where the d…
Multi-Intent Attribute-Aware Text Matching in Searching
Mingzhe Li, Xiuying Chen, Jing Xiang +6
Text matching systems have become a fundamental service in most searching platforms. For instance, they are responsible for matching user queries to relevant candidate items, or re…
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts
Zhitian Xie, Yinger Zhang, Chenyi Zhuang +4
The application of mixture-of-experts (MoE) is gaining popularity due to its ability to improve model's performance. In an MoE structure, the gate layer plays a significant role in…
A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval
Xiaojie Sun, Keping Bi, Jiafeng Guo +5
Dense retrieval methods have been mostly focused on unstructured text and less attention has been drawn to structured data with various aspects, e.g., products with aspects such as…
From Beginner to Expert: Modeling Medical Knowledge into General LLMs
Qiang Li, Xiaoyan Yang, Haowen Wang +14
Recently, large language model (LLM) based artificial intelligence (AI) systems have demonstrated remarkable capabilities in natural language understanding and generation. However,…
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation
Chunjing Gan, Bo Huang, Binbin Hu +6
To help merchants/customers to provide/access a variety of services through miniapps, online service platforms have occupied a critical position in the effective content delivery,…
Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation
Chunjing Gan, Dan Yang, Binbin Hu +6
Nowadays, the rapid development of mobile economy has promoted the flourishing of online marketing campaigns, whose success greatly hinges on the efficient matching between user pr…
ULMA: Unified Language Model Alignment with Human Demonstration and Point-wise Preference
Tianchi Cai, Xierui Song, Jiyan Jiang +3
Aligning language models to human expectations, e.g., being helpful and harmless, has become a pressing challenge for large language models. A typical alignment procedure consists…
Think-in-Memory: Recalling and Post-thinking Enable LLMs with Long-Term Memory
Lei Liu, Xiaoyan Yang, Yue Shen +4
Memory-augmented Large Language Models (LLMs) have demonstrated remarkable performance in long-term human-machine interactions, which basically relies on iterative recalling and re…
On the Opportunities of Green Computing: A Survey
You Zhou, Xiujing Lin, Xiang Zhang +38
Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades, and is widely used in many areas including…