2 citations · 3 across the 15 of their papers we have counts for
9 papers · 1 filter
HalluClean: A Unified Framework to Combat Hallucinations in LLMs
Yaxin Zhao, Yu Zhang
Large language models (LLMs) have achieved impressive performance across a wide range of natural language processing tasks, yet they often produce hallucinated content that undermi…
RPTS: Tree-Structured Reasoning Process Scoring for Faithful Multimodal Evaluation
Haofeng Wang, Yu Zhang
Large Vision-Language Models (LVLMs) excel in multimodal reasoning and have shown impressive performance on various multimodal benchmarks. However, most of these benchmarks evaluat…
Toward Robust Multilingual Adaptation of LLMs for Low-Resource Languages
Haolin Li, Haipeng Zhang, Mang Li +4
Large language models (LLMs) continue to struggle with low-resource languages, primarily due to limited training data, translation noise, and unstable cross-lingual alignment. To a…
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models
Weigao Sun, Jiaxi Hu, Yucheng Zhou +12
Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer m…
X-Intelligence 3.0: Training and Evaluating Reasoning LLM for Semiconductor Display
Xiaolin Yan, Yangxing Liu, Jiazhang Zheng +53
Large language models (LLMs) have recently achieved significant advances in reasoning and demonstrated their advantages in solving challenging problems. Yet, their effectiveness in…
MOSLIM:Align with diverse preferences in prompts through reward classification
Yu Zhang, Wanli Jiang, Zhengyu Yang
The multi-objective alignment of Large Language Models (LLMs) is essential for ensuring foundational models conform to diverse human preferences. Current research in this field typ…
Multimodal Human-AI Synergy for Medical Imaging Quality Control: A Hybrid Intelligence Framework with Adaptive Dataset Curation and Closed-Loop Evaluation
Zhi Qin, Qianhui Gui, Mouxiao Bian +14
Medical imaging quality control (QC) is essential for accurate diagnosis, yet traditional QC methods remain labor-intensive and subjective. To address this challenge, in this study…
A Survey on Post-training of Large Language Models
Guiyao Tie, Zeli Zhao, Dingjie Song +23
The emergence of Large Language Models (LLMs) has fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational system…
Building Decision Making Models Through Language Model Regime
Yu Zhang, Haoxiang Liu, Feijun Jiang +2
We propose a novel approach for decision making problems leveraging the generalization capabilities of large language models (LLMs). Traditional methods such as expert systems, pla…