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Wei Lu

6 papers indexed

arxivcs.CV2026-07-09

HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales

Wenbo Xu, Zhimin Chen, Xiaojie Liang, Hengrui Liu, Wei Lu

Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unprecedented challenges to digital content forensics. Existing benchmarks primarily focus on either face-swapping or global text-t…

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arxivcs.AI2026-07-07

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail

He Liu, Changtao Miao, Xinjie Yang, Tianle Song, Yin Wu, Junchi Chen, et al.

Large language models deployed in open-world applications require safety guardrails that are both robust to complex risks and efficient enough for low-latency runtime moderation. Existing guardrails face a practical trade-off between lightweight classification-based models, which…

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arxivcs.CVcs.AI2026-07-03

R3D: Quantitative 3D Spatial Reasoning for Egocentric Wearables

Maxwell Horton, Wei Lu, Quan Tran, Yury Astashonok, Kirmani Ahmed, Babak Damavandi, et al.

Quantitative 3D spatial reasoning from egocentric RGB-D video is a critical capability for next-generation wearable assistants. Yet existing benchmarks do not reflect the challenges of handling (1) natural egocentric video, (2) posed RGB-D video inputs, and (3) challenging quanti…

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arxivcs.LGcs.CL2026-06-30

RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference

Wenhao Li, Jinhao Dong, Hailin Zhang, Wenhang Shi, Wei Lu, Xiaoyong Du

Long-context Large Language Model inference is severely bottlenecked by the massive Key-Value (KV) cache, yet existing sparse attention methods often suffer from static fixed-budget (Top-k) retrieval or rely on proxy scores that are computationally expensive and biased. To addres…

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arxivcs.RO2026-06-26

Building a Scalable, Reproducible, Evaluatable, and Closed-Loop Simulation Environment Foundation for Embodied Intelligence

Junwu Xiong, Yongjian Guo, Mingxi Luo, Ning Qiao, Lei Kang, Song Wang, et al.

This paper presents a cloud-native simulation infrastructure framework for embodied intelligence that supports large-scale training, standardized evaluation, and simulation-based data collection. The framework unifies simulation environment generation, task execution, trajectory…

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