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20232026
most citedMULTI: Multimodal Understanding Leaderboard with Text and Images

4 citations · 8 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.LG2026

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…

cs.CR2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.CR2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.LG2026

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…