10 papers
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
The Blessing of Dimensionality: How Near-Orthogonality in High-Dimensional Spaces Explains Temporal Portability
Abigail Woodring, Adrian Chan, Rana Muhammad Shahroz Khan +3
Fine-tuning has been widely used to adapt large language models (LLMs) for domain-specific tasks. Parameter efficient fine-tuning (PEFT) methods such as low-rank adaptation (LoRA)…
Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review
Xinyu Zhao, Rana Muhammad Shahroz Khan, Zhen Xu +2
The integration of Large Language Models (LLMs) and Multimodal LLMs (MLLMs) into scientific peer-review workflows introduces novel and significant risks for adversarial manipulatio…
TMS: Trajectory-Mixed Supervision for Reward-Free, On-Policy SFT
Rana Muhammad Shahroz Khan, Zijie Liu, Zhen Tan +2
Reinforcement Learning (RL) and Supervised Fine-Tuning (SFT) are the two dominant paradigms for enhancing Large Language Model (LLM) performance on downstream tasks. While RL gener…
The Quest for Efficient Reasoning: A Data-Centric Benchmark to CoT Distillation
Ruichen Zhang, Rana Muhammad Shahroz Khan, Zhen Tan +3
Data-centric distillation, including data augmentation, selection, and mixing, offers a promising path to creating smaller, more efficient student Large Language Models (LLMs) that…
ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion
Rana Muhammad Shahroz Khan, Dongwen Tang, Pingzhi Li +2
Parameter generation has emerged as a novel paradigm for neural network development, offering an alternative to traditional neural network training by synthesizing high-quality mod…