2 citations · 9 across the 25 of their papers we have counts for
12 papers · 1 filter
The Singularity Has a Distribution: Exact Timing Laws and Detection Limits for a Stochastic Intelligence Explosion
Xiaoyu Li, Zheng Gao, Chiwun Yang +1
Automating AI research creates a positive feedback loop between software capability and research effort. We study a stochastic realisation of this loop in which independent, positi…
A Categorical Atlas of Parameter-Efficient Fine-Tuning: Cones, Orbits, and Gauges
Xiaoyu Li, Zhizhou Sha, Chiwun Yang +1
Parameter-efficient fine-tuning has hundreds of methods, usually compared by parameter count and benchmark score. We compare them as maps. A pretrained checkpoint is a base point i…
The Birkhoff Geometry of Manifold-Constrained Hyper-Connections: Two Channels, Vertex Viscosity, and Sinkhorn as a Retraction
Xiaoyu Li, Zhizhou Sha, Chiwun Yang
Hyper-connections widen the residual stream of a Transformer to parallel streams. Their manifold-constrained version (mHC) mixes the streams at each layer with a doubly stochas…
QATFactory: A Versatile, Deployment-Aligned Framework for Quantization-aware Training and Distillation of LLMs
Weili Xu, Jisen Li, Yuqing Jian +8
Large language model (LLM) inference is increasingly moving toward lower precision to realize the throughput of hardware accelerators, but aggressive post-training quantization (PT…
Nearly Tight Rademacher Bounds for Sparsely Activated Neural Networks
Xiaoyu Li, Zhizhou Sha, Jiaojiao Jiang +2
An input may activate few hidden units even when different inputs collectively use an entire network. We study the statistical complexity of this input-dependent sparsity in the on…
Mapping the City Through the Lens of Language Models
Wanqi Liu, Rong Zhao, Zhizhou Sha +2
Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and function. We measure those a…
ISO: An RLVR-Native Optimization Stack
Hanqing Zhu, Wenyan Cong, Zhizhou Sha +8
Reinforcement learning with verifiable rewards (RLVR) advances the reasoning capabilities of language models, yet the optimization layer that converts reward feedback into weight-s…
Learning from the Self-future: On-policy Self-distillation for dLLMs
Yifu Luo, Zeyu Chen, Haoyu Wang +4
On-policy self-distillation (OPSD) has proven effective for post-training large language models (LLMs), yet its application to diffusion LLMs (dLLMs) remains unexplored. Existing O…
No Hidden Prompts Needed! You Can Game AI Peer Review with Presentation-Only Revisions
Xu Yang, Zhizhou Sha, Junbo Li +10
As AI-generated reviews move from experimental tools into peer-review infrastructure, most robustness concerns have focused on explicit attacks such as hidden instructions and prom…
Culturally uneven urban perception in large language models
Rong Zhao, Wanqi Liu, Zhizhou Sha +3
Large language models (LLMs) are increasingly used to describe and evaluate cities, yet the cultural structure of their urban judgments remains understudied. Here we introduce a me…
MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games
Yunfei Xie, Kevin Wang, Bobby Cheng +9
Multi-turn, multi-agent LLM game evaluations often exhibit substantial run-to-run variance. In long-horizon interactions, small early deviations compound across turns and are ampli…
UrbanAlign: Post-hoc Semantic Calibration for VLM-Human Preference Alignment
Yecheng Zhang, Rong Zhao, Zhizhou Sha +10
Vision-language models (VLMs) can describe urban scenes in rich detail, yet consistently fail to produce reliable human preference labels in domain-specific tasks such as safety as…