2 citations · 6 across the 13 of their papers we have counts for
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LLM Braces: Straightening Out LLM Predictions with Relevant Sub-Updates
Ying Shen, Lifu Huang
Recent findings reveal that much of the knowledge in a Transformer-based Large Language Model (LLM) is encoded in its feed-forward (FFN) layers, where each FNN layer can be interpr…
Modality-Specialized Synergizers for Interleaved Vision-Language Generalists
Zhiyang Xu, Minqian Liu, Ying Shen +5
Recent advancements in Vision-Language Models (VLMs) have led to the emergence of Vision-Language Generalists (VLGs) capable of understanding and generating both text and images. H…
InternalInspector : Robust Confidence Estimation in LLMs through Internal States
Mohammad Beigi, Ying Shen, Runing Yang +7
Despite their vast capabilities, Large Language Models (LLMs) often struggle with generating reliable outputs, frequently producing high-confidence inaccuracies known as hallucinat…
Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning
Zhiyang Xu, Chao Feng, Rulin Shao +6
Despite vision-language models' (VLMs) remarkable capabilities as versatile visual assistants, two substantial challenges persist within the existing VLM frameworks: (1) lacking ta…
X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects
Minqian Liu, Ying Shen, Zhiyang Xu +5
Natural Language Generation (NLG) typically involves evaluating the generated text in various aspects (e.g., consistency and naturalness) to obtain a comprehensive assessment. Howe…
MULTISCRIPT: Multimodal Script Learning for Supporting Open Domain Everyday Tasks
Jingyuan Qi, Minqian Liu, Ying Shen +2
Automatically generating scripts (i.e. sequences of key steps described in text) from video demonstrations and reasoning about the subsequent steps are crucial to the modern AI vir…
The Art of SOCRATIC QUESTIONING: Recursive Thinking with Large Language Models
Jingyuan Qi, Zhiyang Xu, Ying Shen +4
Chain-of-Thought (CoT) prompting enables large language models to solve complex reasoning problems by generating intermediate steps. However, confined by its inherent single-pass a…