10 citations · 17 across the 25 of their papers we have counts for
12 papers · 1 filter
TechImage-Bench: Rubric-Based Evaluation for Technical Image Generation
Minheng Ni, Zhengyuan Yang, Yaowen Zhang +9
We study technical image generation, where a model must synthesize information-dense, scientifically precise illustrations from detailed descriptions rather than merely produce vis…
SHANKS: Simultaneous Hearing and Thinking for Spoken Language Models
Cheng-Han Chiang, Xiaofei Wang, Linjie Li +7
Current large language models (LLMs) and spoken language models (SLMs) begin thinking and taking actions only after the user has finished their turn. This prevents the model from i…
EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing
Tianyu Chen, Yasi Zhang, Zhi Zhang +13
Instruction-based image editing has advanced rapidly, yet reliable and interpretable evaluation remains a bottleneck. Current protocols either (i) depend on paired reference images…
STITCH: Simultaneous Thinking and Talking with Chunked Reasoning for Spoken Language Models
Cheng-Han Chiang, Xiaofei Wang, Linjie Li +7
Spoken Language Models (SLMs) are designed to take speech inputs and produce spoken responses. However, current SLMs lack the ability to perform an internal, unspoken thinking proc…
ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs
Xiyao Wang, Zhengyuan Yang, Chao Feng +10
Reinforcement learning (RL) has shown great effectiveness for fine-tuning large language models (LLMs) using tasks that are challenging yet easily verifiable, such as math reasonin…
What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding
Ming Li, Zhengyuan Yang, Xiyao Wang +4
Large reasoning models (LRMs) achieve strong reasoning performance by emitting long chains of thought. Yet, these verbose traces slow down inference and often drift into unnecessar…
Audio-Aware Large Language Models as Judges for Speaking Styles
Cheng-Han Chiang, Xiaofei Wang, Chung-Ching Lin +8
Audio-aware large language models (ALLMs) can understand the textual and non-textual information in the audio input. In this paper, we explore using ALLMs as an automatic judge to…
SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
Xiyao Wang, Zhengyuan Yang, Chao Feng +6
We introduce ThinkLite-VL, a family of visual reasoning models that achieve state-of-the-art (SoTA) performance using an order of magnitude fewer training samples, relying purely o…
Point-RFT: Improving Multimodal Reasoning with Visually Grounded Reinforcement Finetuning
Minheng Ni, Zhengyuan Yang, Linjie Li +4
Recent advances in large language models have significantly improved textual reasoning through the effective use of Chain-of-Thought (CoT) and reinforcement learning. However, exte…
Measurement of LLM's Philosophies of Human Nature
Minheng Ni, Ennan Wu, Zidong Gong +6
The widespread application of artificial intelligence (AI) in various tasks, along with frequent reports of conflicts or violations involving AI, has sparked societal concerns abou…
Zero-Shot Audio-Visual Editing via Cross-Modal Delta Denoising
Yan-Bo Lin, Kevin Lin, Zhengyuan Yang +6
In this paper, we introduce zero-shot audio-video editing, a novel task that requires transforming original audio-visual content to align with a specified textual prompt without ad…
ImageGen-CoT: Enhancing Text-to-Image In-context Learning with Chain-of-Thought Reasoning
Jiaqi Liao, Zhengyuan Yang, Linjie Li +4
In this work, we study the problem of Text-to-Image In-Context Learning (T2I-ICL). While Unified Multimodal LLMs (MLLMs) have advanced rapidly in recent years, they struggle with c…