4 citations · 8 across the 13 of their papers we have counts for
14 papers
HarnessTTT: Learn to Optimize Harness at Test-Time for Scientific Discovery
Yingzi Ma, Yulong Cao, Nanxi Li +5
Scientific discovery with language models requires finding the best valid solution within a finite computational budget. We study how feedback from this search can improve the proc…
EvoSafeHarness: Evolving Model- and Domain-Specific Harnesses for Securing Agents
Nanxi Li, Yingzi Ma, Yulong Cao +7
Large language model (LLM) agents can translate natural-language requests into real-world actions, creating safety risks from both indirect prompt injections and directly harmful r…
Off-Manifold Collapse in Guided Protein Language Models
Shuibai Zhang, Xinchi Liu, Fred Zhangzhi Peng +4
Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative to fine-tuning. Such guidan…
One Student, Many Teachers: Multi-Task On-Policy Distillation via Soft-Prompt Privileged Context
Yingzi Ma, Zichen Zhu, Ming Jiang +1
On-policy self-distillation (OPSD) teaches large language models new skills through a teacher that shares the student's backbone and supervises its own rollouts. Existing teachers…
MaskForge: Structure-Aware Adaptive Attacks for Jailbreaking Diffusion Large Language Models
Yingzi Ma, Zhengyue Zhao, Xiaogeng Liu +3
Diffusion large language models (dLLMs) generate text by iteratively denoising partially masked sequences under bidirectional context, exposing a safety surface distinct from autor…
GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving
Yingzi Ma, Chaowei Xiao, Ming Jiang
Vision-language models (VLMs) for autonomous driving have shown promising performance, but their ability to handle region-specific traffic rules remains underexplored, raising unce…
SafeGen-Bench: Benchmarking Safety in Image-Conditioned Text-to-Video Generation
Yingzi Ma, Xiaogeng Liu, Yawen Zheng +1
With the rapid advancements in text-to-image diffusion models, generative video models (T2V models) like Sora can now produce short synthetic videos from a text prompt or an initia…
When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning
Xiaogeng Liu, Xinyan Wang, Yingzi Ma +2
On-policy self-distillation (OPSD) trains a student on its own rollouts using a privileged teacher, but its standard objective weights all generated tokens equally, implicitly trea…
dVLM-AD: Enhance Diffusion Vision-Language-Model for Driving via Controllable Reasoning
Yingzi Ma, Yulong Cao, Wenhao Ding +6
The autonomous driving community is increasingly focused on addressing the challenges posed by out-of-distribution (OOD) driving scenarios. A dominant research trend seeks to enhan…
ARMOR: Aligning Secure and Safe Large Language Models via Meticulous Reasoning
Zhengyue Zhao, Yingzi Ma, Somesh Jha +3
Large Language Models have shown impressive generative capabilities across diverse tasks, but their safety remains a critical concern. Existing post-training alignment methods, suc…
Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
Yingzi Ma, Jiongxiao Wang, Fei Wang +10
Machine unlearning has emerged as an effective strategy for forgetting specific information in the training data. However, with the increasing integration of visual data, privacy c…
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Dengchun Li, Yingzi Ma, Naizheng Wang +8
Fine-tuning Large Language Models (LLMs) is a common practice to adapt pre-trained models for specific applications. While methods like LoRA have effectively addressed GPU memory c…
MULTI: Multimodal Understanding Leaderboard with Text and Images
Zichen Zhu, Yang Xu, Lu Chen +11
The rapid development of multimodal large language models (MLLMs) raises the question of how they compare to human performance. While existing datasets often feature synthetic or o…
Dolphins: Multimodal Language Model for Driving
Yingzi Ma, Yulong Cao, Jiachen Sun +2
The quest for fully autonomous vehicles (AVs) capable of navigating complex real-world scenarios with human-like understanding and responsiveness. In this paper, we introduce Dolph…