7 citations · 9 across the 8 of their papers we have counts for
9 papers
The Bias is in the Details: An Assessment of Cognitive Bias in LLMs
R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3
As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…
In-Depth and In-Breadth: Pre-training Multimodal Language Models Customized for Comprehensive Chart Understanding
Wan-Cyuan Fan, Yen-Chun Chen, Mengchen Liu +3
Recent methods for customizing Large Vision Language Models (LVLMs) for domain-specific tasks have shown promising results in scientific chart comprehension. However, existing appr…
Phi-4-Mini-Reasoning: Exploring the Limits of Small Reasoning Language Models in Math
Haoran Xu, Baolin Peng, Hany Awadalla +11
Chain-of-Thought (CoT) significantly enhances formal reasoning capabilities in Large Language Models (LLMs) by training them to explicitly generate intermediate reasoning steps. Wh…
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
Microsoft, :, Abdelrahman Abouelenin +73
We introduce Phi-4-Mini and Phi-4-Multimodal, compact yet highly capable language and multimodal models. Phi-4-Mini is a 3.8-billion-parameter language model trained on high-qualit…
ReXTime: A Benchmark Suite for Reasoning-Across-Time in Videos
Jr-Jen Chen, Yu-Chien Liao, Hsi-Che Lin +3
We introduce ReXTime, a benchmark designed to rigorously test AI models' ability to perform temporal reasoning within video events. Specifically, ReXTime focuses on reasoning acros…
On Pre-training of Multimodal Language Models Customized for Chart Understanding
Wan-Cyuan Fan, Yen-Chun Chen, Mengchen Liu +2
Recent studies customizing Multimodal Large Language Models (MLLMs) for domain-specific tasks have yielded promising results, especially in the field of scientific chart comprehens…
Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
Max Liu, Chan-Hung Yu, Wei-Hsu Lee +3
Programmatic reinforcement learning (PRL) has been explored for representing policies through programs as a means to achieve interpretability and generalization. Despite promising…
iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse Views
Chin-Hsuan Wu, Yen-Chun Chen, Bolivar Solarte +2
We present iFusion, a novel 3D object reconstruction framework that requires only two views with unknown camera poses. While single-view reconstruction yields visually appealing re…
LACMA: Language-Aligning Contrastive Learning with Meta-Actions for Embodied Instruction Following
Cheng-Fu Yang, Yen-Chun Chen, Jianwei Yang +4
End-to-end Transformers have demonstrated an impressive success rate for Embodied Instruction Following when the environment has been seen in training. However, they tend to strugg…