3 citations · 4 across the 22 of their papers we have counts for
9 papers · 1 filter
Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems
Shuang Yang, Zijie Zhuang, Changxin Lao +20
Sustaining industrial recommendation research requires using the results of one experiment to decide what to investigate next. We present AgentX-Model, the next generation of Agent…
TRACER: Trajectory-Aligned Learning for Multi-Turn User Simulation
Geng Chen, Ruotong Pan, Zhirui Yang +9
Faithful user simulation is fundamental to building, evaluating, and improving interactive AI at scale. Yet current simulators often produce plausible individual responses without…
Reason What Matters: Retrieval-Grounded Reasoning for Universal Multimodal Embeddings
Mingzhou Jiang, Peixi Wu, Hang Cheng +7
Universal multimodal embedding (UME) maps multimodal inputs into a shared embedding space for diverse retrieval tasks. Recent methods improve embeddings through Chain-of-Thought (C…
RobustSGPO: Search-Space Control for Agent Harness Evolution
Zibo Zhao, Jijun Shi, Mo Zhou +9
Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edit scope and operation unreso…
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…
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…
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…
Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology
Tianhao Shi, Yang Zhang, Xiaoyan Zhao +8
The rapid proliferation of Artificial Intelligence-Generated Content (AIGC) is fundamentally restructuring online content ecologies, necessitating a rigorous examination of its beh…
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…