13 citations · 24 across the 10 of their papers we have counts for
11 papers
Pick the Mixture, Not the Samples: Combinatorial Data Selection for LLMs
Luyang Zhang, Jialu Wang, Bebei Li
Data selection for LLM fine-tuning faces two facts about real training: data pools draw from many distinct domains, and evaluation spans diverse tasks. As a result, the same sample…
Post-Training Recipe, More Than Model Family, Shapes Multi-Agent LLM Conversational Behavior
Luyang Zhang, Jialu Wang, Fei Xue +1
Multi-LLM systems use multiple language models to deliberate, judge each other's outputs, or coordinate as agents. Their value depends on the models producing measurably different…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +355
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
When Attribution Patching Lies: Diagnosis and a Second-Order Correction
Luyang Zhang, Jialu Wang
A central goal of mechanistic interpretability is to identify which internal components causally drive a language model's behavior. Because these importance estimates serve as the…
UniPinRec: Unifying Generative Retrieval and Ranking at Pinterest Scale
Hanyu Li, Yi-Ping Hsu, Aditya Mantha +17
Modern recommendation systems predominantly train retrieval and ranking as separate models despite both increasingly relying on large transformers encoding the same user behavior d…
MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer
Xuefei Wang, Jialu Wang, Fengbo Zhang +6
Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance critically depends on the under…
Do Agents Repair When Challenged -- or Just Reply? Challenge, Repair, and Public Correction in a Deployed Agent Forum
Luyang Zhang, Yi-Yun Chu, Jialu Wang +2
As large language model (LLM) agents enter public forums, a key question is whether those forums sustain challenge, repair, and public correction, or merely produce norm-like langu…
SPOT: Span-level Pause-of-Thought for Efficient and Interpretable Latent Reasoning in Large Language Models
Yunlong Chu, Minglai Shao, Yuhang Liu +4
Explicit Chain-of-Thought improves the reasoning performance of large language models but often incurs high inference cost due to verbose token-level traces. While recent approache…
AgenticGEO: A Self-Evolving Agentic System for Generative Engine Optimization
Jiaqi Yuan, Jialu Wang, Zihan Wang +3
Generative search engines represent a transition from traditional ranking-based retrieval to Large Language Model (LLM)-based synthesis, transforming optimization goals from rankin…
JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents
Kaizhi Zheng, Kaiwen Zhou, Jing Gu +5
Building a conversational embodied agent to execute real-life tasks has been a long-standing yet quite challenging research goal, as it requires effective human-agent communication…
AceKG: A Large-scale Knowledge Graph for Academic Data Mining
Ruijie Wang, Yuchen Yan, Jialu Wang +4
Most existing knowledge graphs (KGs) in academic domains suffer from problems of insufficient multi-relational information, name ambiguity and improper data format for large-scale…