28 citations · 37 across the 16 of their papers we have counts for
5 papers · 1 filter
BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning
Xuechen Zhang, Zijian Huang, Yingcong Li +3
Small language models (SLMs) struggle to learn complex reasoning behaviors, especially when high-quality traces are scarce or difficult to learn from. The standard training approac…
Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement
Xuechen Zhang, Zijian Huang, Chenshun Ni +3
Recent research enhances language model reasoning by scaling test-time compute via longer chain-of-thought traces. This often improves accuracy but also introduces redundancy and h…
Continuous Chain of Thought Enables Parallel Exploration and Reasoning
Halil Alperen Gozeten, M. Emrullah Ildiz, Xuechen Zhang +3
Modern language models generate chain-of-thought traces by autoregressively sampling tokens from a finite vocabulary. While this discrete sampling has achieved remarkable success,…
L3GS: Layered 3D Gaussian Splats for Efficient 3D Scene Delivery
Yi-Zhen Tsai, Xuechen Zhang, Zheng Li +1
Traditional 3D content representations include dense point clouds that consume large amounts of data and hence network bandwidth, while newer representations such as neural radianc…
Test-Time Training Provably Improves Transformers as In-context Learners
Halil Alperen Gozeten, M. Emrullah Ildiz, Xuechen Zhang +3
Test-time training (TTT) methods explicitly update the weights of a model to adapt to the specific test instance, and they have found success in a variety of settings, including mo…