From the 1 of 6 linked papers with an AI index.
6 papers
NeMo: Needle in a Montage for Video-Language Understanding
Zi-Yuan Hu, Shuo Liang, Duo Zheng +10
The paper introduces the Needle in a Montage (NeMo) task and the NeMoBench benchmark to evaluate temporal understanding in video-language models, using an automated pipeline to gen…
VideoLatent: Video-Language Learning via Latent Self-Forcing
Zi-Yuan Hu, Zicong Tang, Shijia Huang +3
Recent advancements in chain-of-thought (CoT) reasoning have shown promise in enhancing video understanding and reasoning capabilities of multimodal large language models (MLLMs).…
Membership Inference on LLMs in the Wild
Jiatong Yi, Yanyang Li
Membership Inference Attacks (MIAs) act as a crucial auditing tool for the opaque training data of Large Language Models (LLMs). However, existing techniques predominantly rely on…
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors
Duo Zheng, Shijia Huang, Yanyang Li +1
Previous research has investigated the application of Multimodal Large Language Models (MLLMs) in understanding 3D scenes by interpreting them as videos. These approaches generally…
Learning to Reason from Feedback at Test-Time
Yanyang Li, Michael Lyu, Liwei Wang
Solving complex tasks in a single attempt is challenging for large language models (LLMs). Iterative interaction with the environment and feedback is often required to achieve succ…
CLEVA: Toward Comprehensive and Contamination-Free Language Model Evaluation
Yanyang Li, Tin Long Wong, Cheung To Hung +5
Recent advances in large language models (LLMs) have shown significant promise, yet their evaluation raises concerns, particularly regarding data contamination due to the lack of a…