activity
20242026
most citedLoRC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2026

TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts

Hua-Rong Chu, Kuan-Chun Wang, Yao-Te Huang

Safety guardrails have become an active area of research in AI safety, aimed at ensuring the appropriate behavior of large language models (LLMs). However, existing research lacks…

cs.LG2025

Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Yiping Wang, Qing Yang, Zhiyuan Zeng +11

We show that reinforcement learning with verifiable reward using one training example (1-shot RLVR) is effective in incentivizing the math reasoning capabilities of large language…

cs.CV2024

Is Your World Simulator a Good Story Presenter? A Consecutive Events-Based Benchmark for Future Long Video Generation

Yiping Wang, Xuehai He, Kuan Wang +5

The current state-of-the-art video generative models can produce commercial-grade videos with highly realistic details. However, they still struggle to coherently present multiple…

cs.CV2024

Mojito: Motion Trajectory and Intensity Control for Video Generation

Xuehai He, Shuohang Wang, Jianwei Yang +7

Recent advancements in diffusion models have shown great promise in producing high-quality video content. However, efficiently training video diffusion models capable of integratin…

cs.LG20241 cited

LoRC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy

Rongzhi Zhang, Kuang Wang, Liyuan Liu +4

The Key-Value (KV) cache is a crucial component in serving transformer-based autoregressive large language models (LLMs), enabling faster inference by storing previously computed K…