1 citations · 2 across the 15 of their papers we have counts for
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RLLaVA: An RL-central Framework for Language and Vision Assistants
Lei Zhao, Zihao Ma, Boyu Lin +3
We present an RL-central framework for Language and Vision Assistants (RLLaVA) with its formulation of Markov decision process (MDP). RLLaVA decouples RL algorithmic logic from mod…
Tool-Augmented Hybrid Ensemble Reasoning with Distillation for Bilingual Mathematical Problem Solving
Peiqing Lu, Yuan Zhang, Haoyun Zhang +3
Bilingual mathematical problem solving needs a clear link between language reasoning and symbolic calculation. Large language models often handle language well but are weak in accu…
What Color Is the Text? A Benchmark for Hallucination Induced by Image-Embedded Prompt
Jinkun Zhao, Lei Huang, Haixin Ge +1
We introduce Embedded Stroop, a controlled diagnostic paradigm for measuring image-embedded prompt interference in Multimodal Large Language Models (MLLMs), where the query is rend…
IMAGINE: Integrating Multi-Agent System into One Model for Complex Reasoning and Planning
Xikai Zhang, Bo Wang, Likang Xiao +4
Although large language models (LLMs) have made significant strides across various tasks, they still face significant challenges in complex reasoning and planning. For example, eve…
EDGE-GRPO: Entropy-Driven GRPO with Guided Error Correction for Advantage Diversity
Xingjian Zhang, Siwei Wen, Wenjun Wu +1
Large Language Models (LLMs) have made remarkable progress in enhancing step-by-step reasoning through reinforcement learning. However, the Group Relative Policy Optimization (GRPO…
CoE-Ops: Collaboration of LLM-based Experts for AIOps Question-Answering
Jinkun Zhao, Yuanshuai Wang, Xingjian Zhang +6
With the rapid evolution of artificial intelligence, AIOps has emerged as a prominent paradigm in DevOps. Lots of work has been proposed to improve the performance of different AIO…
VoQA: Visual-only Question Answering
Jianing An, Luyang Jiang, Jie Luo +2
Visual understanding requires interpreting both natural scenes and the textual information that appears within them, motivating tasks such as Visual Question Answering (VQA). Howev…
Parallel Layer Normalization for Universal Approximation
Yunhao Ni, Yuxin Guo, Yuhe Liu +4
Layer Normalization (LN) is usually studied for its role in optimization, but it also acts as a multivariate nonlinearity between affine layers. We investigate how grouping LN unit…
TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning
Xingjian Zhang, Siwei Wen, Wenjun Wu +1
Recently, improving the reasoning ability of large multimodal models (LMMs) through reinforcement learning has made great progress. However, most existing works are based on highly…
Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation
Siwei Wen, Junyan Ye, Peilin Feng +7
With the rapid advancement of Artificial Intelligence Generated Content (AIGC) technologies, synthetic images have become increasingly prevalent in everyday life, posing new challe…
TinyLLaVA-Video: Towards Smaller LMMs for Video Understanding with Group Resampler
Xingjian Zhang, Xi Weng, Yihao Yue +3
Video behavior recognition and scene understanding are fundamental tasks in multimodal intelligence, serving as critical building blocks for numerous real-world applications. Throu…