36 citations · 42 across the 17 of their papers we have counts for
5 papers · 1 filter
PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data
Kai Xiong, Yanwei Huang, Rongjunchen Zhang +3
High-quality mathematical and logical datasets with verifiable answers are essential for strengthening the reasoning capabilities of large language models (LLMs). While recent data…
Com: A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models
Kai Xiong, Xiao Ding, Yixin Cao +7
Large language models (LLMs) have mastered abundant simple and explicit commonsense knowledge through pre-training, enabling them to achieve human-like performance in simple common…
Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning
Yang He, Xiao Ding, Bibo Cai +5
While reasoning-augmented large language models (RLLMs) significantly enhance complex task performance through extended reasoning chains, they inevitably introduce substantial unne…
UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection
Yang Zhao, Kai Xiong, Xiao Ding +9
Scaling RL for LLMs is computationally expensive, largely due to multi-sampling for policy optimization and evaluation, making efficient data selection crucial. Inspired by the Zon…
Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection
Yang Zhao, Li Du, Xiao Ding +10
Large language models (LLMs) have shown great potential across various industries due to their remarkable ability to generalize through instruction tuning. However, the limited ava…