collaborators

8 papers

cs.LG2026

GIFT: Gradient Informed Filtering for Distillation Augmented Reasoning RL

Shijie Li, Yilin Gao, Tieyuan Chen +3

Training large language models for complex reasoning tasks relies on two complementary signals: sparse, outcome-grounded reinforcement learning (RL) for correctness, and dense, tok…

cs.CV2026

VGGA: Geometry-Grounded Autoencoder for Video Generation

Chaofan Gan, Yian Zhao, Shijie Li +4

Autoencoders are the core component of latent video generative models, compressing high-dimensional videos into compact latent spaces for downstream generation. However, existing v…

cs.CV2026

Multimodal Continuous Reasoning via Asymmetric Mutual Variational Learning

Shijie Li, Yilin Gao, Siyuan Yang +7

Multimodal Large Language Models (MLLMs) are often constrained by a language-space bottleneck, forcing complex visual reasoning into discrete tokens which can lose perceptual nuanc…

cs.CV2026

From Priors to Perception: Grounding Video-LLMs in Physical Reality

Zicheng Zhao, Chaofan Gan, Shijie Li +1

Video Large Language Models (Video-LLMs) excel in general video understanding but often base physical judgments on event expectations rather than observations. We find that they no…

cs.CV2026

VidLaDA: Bidirectional Diffusion Large Language Models for Efficient Video Understanding

Zhihao He, Tieyuan Chen, Kangyu Wang +6

Current Video Large Language Models (Video LLMs) typically encode frames via a vision encoder and employ an autoregressive (AR) LLM for understanding and generation. However, this…

cs.RO2026

DV-VLN: Dual Verification for Reliable LLM-Based Vision-and-Language Navigation

Zijun Li, Shijie Li, Zhenxi Zhang +2

Vision-and-Language Navigation (VLN) requires an embodied agent to navigate in a complex 3D environment according to natural language instructions. Recent progress in large languag…

cs.CV2025

CogStream: Context-guided Streaming Video Question Answering

Zicheng Zhao, Kangyu Wang, Shijie Li +3

Despite advancements in Video Large Language Models (Vid-LLMs) improving multimodal understanding, challenges persist in streaming video reasoning due to its reliance on contextual…

cs.CV2025

Looking Beyond Visible Cues: Implicit Video Question Answering via Dual-Clue Reasoning

Tieyuan Chen, Huabin Liu, Yi Wang +8

Video Question Answering (VideoQA) aims to answer natural language questions based on the given video, with prior work primarily focusing on identifying the duration of relevant se…