3 citations · 4 across the 8 of their papers we have counts for
6 papers · 1 filter
Representation-Aligned Auxiliary Supervision for Language Model Adaptation
Kyuyoung Kim, Peiyao Sheng, Ashwin Hebbar +9
Language models exhibit strong reasoning capabilities, yet adapting them to structured domains remains challenging and can yield inconsistent outcomes. We identify representation c…
TuringLLM: Efficiently Scaling Foundation Models Toward Physical AI
Yuheng Zhang, Yizhao Wang, Da Zhu +19
We present Turing-20B-A2B, a 20B-parameter Mixture-of-Experts language model that activates approximately 2B parameters per token, designed for long-context and latency-sensitive p…
TuringViT: Making SOTA Vision Transformers Accessible to All
Qiman Wu, Hanlin Chen, Lyujie Chen +19
Modern VLMs and VLA systems commonly adopt off-the-shelf ViTs such as SigLIP2 as visual encoders, but diverse downstream requirements in latency, temporal modeling, and VLM integra…
Where You Inject Diversity Matters: A Unified Framework for Diverse Generation
Cheng Zhang, Rui Xin, Chudi Zhong
Open-ended generation tasks often require a set of meaningfully different outputs, yet large language models often produce similar generations. Existing test-time diversity methods…
EvoLM: Self-Evolving Language Models through Co-Evolved Discriminative Rubrics
Shuyue Stella Li, Rui Xin, Teng Xiao +8
Language models encode substantial evaluative knowledge from pretraining, yet current post-training methods rely on external supervision (human annotations, proprietary models, or…
Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch
Hyunwoo Kim, Niloofar Mireshghallah, Michael Duan +11
Research involving privacy-sensitive data has always been constrained by data scarcity, standing in sharp contrast to other areas that have benefited from data scaling. This challe…