1 citations · 1 across the 7 of their papers we have counts for
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Persistent Object Narratives for Token-Efficient Video Language Models
Junzhe Chen, Siyuan Meng, Xiaojie Guo
Video large language models (Video-LLMs) have made strong progress in open-ended video understanding. However, their visual interfaces remain token-intensive and provide limited ex…
Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution
Tian Qin, Junzhe Chen, Yuqing Shi +3
Large vision-language models (LVLMs) often hallucinate when language priors dominate weak or ambiguous visual evidence. Existing contrastive decoding methods mitigate this problem…
TOC-Bench: A Temporal Object Consistency Benchmark for Video Large Language Models
Junzhe Chen, Siyuan Meng, Yuxi Chen +3
Video large language models (Video-LLMs) have made strong progress in general video understanding, but their ability to maintain temporal object consistency remains underexplored.…
Meta-TTRL: A Metacognitive Framework for Self-Improving Test-Time Reinforcement Learning in Unified Multimodal Models
Lit Sin Tan, Junzhe Chen, Xiaolong Fu +5
Existing test-time scaling (TTS) methods for unified multimodal models (UMMs) in text-to-image (T2I) generation primarily rely on search or sampling strategies that produce only in…