collaborators

12 papers

cs.LG2026

Mechanism Design for Generative Engines: From Exploitation toward Win-Win Outcomes

Chen Xu, Zitian Guo, Chenyan Xiong

Generative engines are reshaping the web ecosystem by making citations a key mechanism for allocating attention, attribution, and downstream value. This creates a strategic tension…

cs.MA2026

One Run Is Not an Idea: The Implementation Lottery in Automated Research

Jingjie Ning, Shanshan Zhong, Xiaochuan Li +2

The paper studies how automated research systems can draw misleading conclusions when they rely on a single implementation of an idea, introducing the concept of an "implementation…

cs.AI2026

Closed-loop Auto Research for Molecular Property Prediction: Discovering and Certifying Generalizable Improvements

Jingjie Ning, Xiaochuan Li, Ji Zeng +2

Closed-loop Auto Research extends automated machine learning from fixed-dataset fitting to changing the research workflow, with language-model agents editing representations and mo…

cs.AI2026

Beyond Parallel Sampling: Diverse Query Initialization for Agentic Search

Sidhaarth Murali, João Coelho, Jingjie Ning +3

Test-time scaling for agentic search typically increases depth (i.e., more turns and tokens per trajectory) or breadth (i.e., more parallel rollouts). Here we focus on breadth scal…

cs.IR2026

Effective Reinforcement Learning for Agentic Search by Recycling Zero-Variance Queries During Training

João Coelho, João Magalhães, Bruno Martins +1

The use of GRPO-style algorithms has become the standard strategy for training LLM search agents under outcome-only rewards. With these algorithms, a query contributes to parameter…

cs.IR2026

Agentic Search in the Wild: Intents and Trajectory Dynamics from 14M+ Real Search Requests

Jingjie Ning, João Coelho, Yibo Kong +5

LLM-powered search agents are increasingly being used for multi-step information seeking tasks, yet the IR community lacks empirical understanding of how agentic search sessions un…