2 citations · 2 across the 8 of their papers we have counts for
8 papers
Penelope: Localized Latent Recurrence for Efficient Structured Reasoning
Yutong Chen, Shouqian Shi, Xinran Liu +5
Complex structured reasoning tasks often require additional computation, yet current language models obtain it mainly by increasing parameter scale or by serializing intermediate s…
CoScale-RL: Efficient Post-Training by Co-Scaling Data and Computation
Yutong Chen, Jiandong Gao, Ji Wu
Training Large Reasoning Model (LRM) is usually unstable and unpredictable, especially on hard problems or weak foundation models. We found that the current post-training scaling s…
Rethinking the Value of Multi-Agent Workflow: A Strong Single Agent Baseline
Jiawei Xu, Arief Koesdwiady, Sisong Bei +8
Recent advances in LLM-based multi-agent systems (MAS) show that workflows composed of multiple LLM agents with distinct roles, tools, and communication patterns can outperform sin…
ENTRA: Entropy-Based Redundancy Avoidance in Large Language Model Reasoning
Ruichu Cai, Haopeng Du, Qingwen Lin +3
Large Reasoning Models (LRMs) often suffer from overthinking, generating unnecessarily long reasoning chains even for simple tasks. This leads to substantial computational overhead…
Collaborative Parameter Learning: Mitigating Forgetting via Parameter-Level Gradient Analysis
Mutian Yang, Zisen Zhan, Yutong Chen +7
Catastrophic forgetting during knowledge injection impairs the ability of large language models to acquire new knowledge without overwriting previously mastered knowledge. Recent s…
Towards Effective Model Editing for LLM Personalization
Baixiang Huang, Limeng Cui, Jiapeng Liu +7
Personalization is becoming indispensable for LLMs to align with individual user preferences and needs. Yet current approaches are often computationally expensive, data-intensive,…
Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning
Yutong Chen, Jiandong Gao, Ji Wu
R1-style Reinforcement Learning (RL) significantly enhances Large Language Models' reasoning capabilities, yet the mechanism behind rule-based RL remains unclear. We found that sma…
Dynamic feature selection in medical predictive monitoring by reinforcement learning
Yutong Chen, Jiandong Gao, Ji Wu
In this paper, we investigate dynamic feature selection within multivariate time-series scenario, a common occurrence in clinical prediction monitoring where each feature correspon…