6 citations · 10 across the 10 of their papers we have counts for
11 papers
Distillation as Probability Transport: Routed On-Policy Distillation
Tianle Xia, Lingxiang Hu, Yiding Sun +6
On-policy distillation (OPD) transfers teacher knowledge on student-generated trajectories, but efficient sampled objectives reduce the teacher distribution to scalar credit on ind…
Teaching a Moving Student: Rethinking the Curriculum of On-Policy Distillation
Lingxiang Hu, Tianle Xia, Ming Xu +6
In on-policy distillation (OPD), the student determines which states receive teacher supervision. As its policy evolves, earlier response prefixes become less likely even though te…
When Self-Evolution Backfires: Pre-Commit Gating against Skill Contamination in LLM Agents
Linfang Shang, Ming Xu, Yiding Sun +4
Self-evolving agents accumulate capability by distilling reusable skills from their execution trajectories, but we find this process is not monotonic: past a critical pool size, ne…
AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents
Lingxiang Hu, Yiding Sun, Tianle Xia +6
While Large Language Model (LLM) agents have made remarkable progress on complex reasoning, evaluating them in real-world environments remains an open problem. Existing benchmarks…
EmoRAG: Evaluating RAG Robustness to Symbolic Perturbations
Xinyun Zhou, Xinfeng Li, Yinan Peng +9
Retrieval-Augmented Generation (RAG) systems are increasingly central to robust AI, enhancing large language model (LLM) faithfulness by incorporating external knowledge. However,…
Agent-in-the-Loop: A Data Flywheel for Continuous Improvement in LLM-based Customer Support
Cen Mia Zhao, Tiantian Zhang, Hanchen Su +8
We introduce an Agent-in-the-Loop (AITL) framework that implements a continuous data flywheel for iteratively improving an LLM-based customer support system. Unlike standard offlin…
Enhancing LLM Reasoning via Non-Human-Like Reasoning Path Preference Optimization
Junjie Lu, Yuliang Liu, Chaofeng Qu +4
Current approaches for strengthening LLM reasoning tend to introduce a training bias toward human-like reasoning trajectories. In step-wise preference optimization, in particular,…
BigCodeArena: Unveiling More Reliable Human Preferences in Code Generation via Execution
Terry Yue Zhuo, Xiaolong Jin, Hange Liu +37
Crowdsourced model evaluation platforms, such as Chatbot Arena, enable real-time evaluation from human perspectives to assess the quality of model responses. In the coding domain,…
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
P Team, Xinrun Du, Yifan Yao +94
Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…
Sparse Autoencoder as a Zero-Shot Classifier for Concept Erasing in Text-to-Image Diffusion Models
Zhihua Tian, Sirun Nan, Ming Xu +5
Text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images but also raise people's concerns about generating harmful or misleading con…
MatPilot: an LLM-enabled AI Materials Scientist under the Framework of Human-Machine Collaboration
Ziqi Ni, Yahao Li, Kaijia Hu +6
The rapid evolution of artificial intelligence, particularly large language models, presents unprecedented opportunities for materials science research. We proposed and developed a…