activity
20232026
most citedOlaGPT: Empowering LLMs With Human-like Problem-Solving Abilities

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

expo: Exploration-prioritized policy optimization via adaptive kl regulation and gaussian curriculum sampling

Mingxiong Lin, Zhangquan Gong, Maowen Tang +6

Reinforcement Learning with Verifiable Rewards (RLVR) has become the standard paradigm for LLM mathematical reasoning, where Group Relative Policy Optimization (GRPO) serves as the…

cs.LG2026

fg-expo: Frontier-guided exploration-prioritized policy optimization via adaptive kl and gaussian curriculum

Mingxiong Lin, Zhangquan Gong, Maowen Tang +6

Reinforcement Learning with Verifiable Rewards (RLVR) has become the standard paradigm for LLM mathematical reasoning, with Group Relative Policy Optimization (GRPO) serving as the…

cs.AI2025

Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval Augmented Generation Across Learning Style

Debdeep Sanyal, Agniva Maiti, Umakanta Maharana +4

Effective teaching requires adapting instructional strategies to accommodate the diverse cognitive and behavioral profiles of students, a persistent challenge in education and teac…

cs.CL2024

Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm

Yuanzhen Xie, Xinzhou Jin, Tao Xie +7

In-context learning of large-language models (LLMs) has achieved remarkable success in the field of natural language processing, while extensive case studies reveal that the single…

cs.CL2023★ 1 cited

OlaGPT: Empowering LLMs With Human-like Problem-Solving Abilities

Yuanzhen Xie, Tao Xie, Mingxiong Lin +7

In most current research, large language models (LLMs) are able to perform reasoning tasks by generating chains of thought through the guidance of specific prompts. However, there…