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20242026
most citedVITA: Towards Open-Source Interactive Omni Multimodal LLM

5 citations · 9 across the 10 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

hep-ph2026

Two-loop helicity amplitudes for using high-energy and forward expansions

Mateusz Czaja, Ben Rott, Matthias Steinhauser +1

We calculate next-to-leading order QCD corrections for the process with two off-shell bosons, accounting for virtual top quarks in the loop diagrams. Our approa…

cs.CV2026

OmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains

Xinyue Cai, Chaoyou Fu, Yi-Fan Zhang +2

Current automated pipelines for audio-visual Question Answering (QA) generally adopt a ``video-caption-QA'' paradigm. However, these methods typically segment videos into short cli…

cs.CV2026

VideoDetective: Clue Hunting via both Extrinsic Query and Intrinsic Relevance for Long Video Understanding

Ruoliu Yang, Chu Wu, Caifeng Shan +2

Long video understanding remains challenging for multimodal large language models (MLLMs) due to limited context windows, which necessitate identifying sparse query-relevant video…

cs.CL2026

SpeechParaling-Bench: A Comprehensive Benchmark for Paralinguistic-Aware Speech Generation

Ruohan Liu, Shukang Yin, Tao Wang +6

Paralinguistic cues are essential for natural human-computer interaction, yet their evaluation in Large Audio-Language Models (LALMs) remains limited by coarse feature coverage and…

cs.CV2026

Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding

Chaoyou Fu, Haozhi Yuan, Yuhao Dong +16

With the rapid advancement of video understanding, existing benchmarks are becoming increasingly saturated, exposing a critical discrepancy between inflated leaderboard scores and…

cs.CV2026

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion

Lijiang Li, Zuwei Long, Yunhang Shen +6

While recent multimodal large language models (MLLMs) have made impressive strides, they predominantly employ a conventional autoregressive architecture as their backbone, leaving…