1 citations · 1 across the 5 of their papers we have counts for
5 papers
GRRR: The Geometry of Reshaping, Rotation, and Routing in Decoder LLM post-training
Jianing Qi, Hao Tang, Zhigang Zhu
We study how post-training changes the weights of Large Language Models (LLMs) relative to their pretrained weights. Across 12 post-training chains with supervised fine-tuning (SFT…
Policy Gradient Guidance Enables Test Time Control
Jianing Qi, Hao Tang, Zhigang Zhu
We introduce Policy Gradient Guidance (PGG), a simple extension of classifier-free guidance from diffusion models to classical policy gradient methods. PGG augments the policy grad…
Learning to Reason Across Parallel Samples for LLM Reasoning
Jianing Qi, Xi Ye, Hao Tang +2
Scaling test-time compute brings substantial performance gains for large language models (LLMs). By sampling multiple answers and heuristically aggregate their answers (e.g., eithe…
Beyond Semantics: Rediscovering Spatial Awareness in Vision-Language Models
Jianing Qi, Jiawei Liu, Hao Tang +1
Vision Language Models (VLMs) excel at identifying and describing objects but often fail at spatial reasoning. We study why VLMs, such as LLaVA, underutilize spatial cues despite h…
VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers
Jianing Qi, Hao Tang, Zhigang Zhu
Recent advancements in test time compute, particularly through the use of verifier models, have significantly enhanced the reasoning capabilities of Large Language Models (LLMs). T…