28 citations · 37 across the 12 of their papers we have counts for
13 papers
AgriWorld:A World Tools Protocol Framework for Verifiable Agricultural Reasoning with Code-Executing LLM Agents
Zhixing Zhang, Jesen Zhang, Hao Liu +4
Foundation models for agriculture are increasingly trained on massive spatiotemporal data (e.g., multi-spectral remote sensing, soil grids, and field-level management logs) and ach…
Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents
Haiyang Xu, Xi Zhang, Haowei Liu +16
The paper introduces GUI-Owl-1.5, the latest native GUI agent model that features instruct/thinking variants in multiple sizes (2B/4B/8B/32B/235B) and supports a range of platforms…
GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation
Hao Liu, Guangyan Li, Wensheng Zhang +1
Large Language Models (LLMs) exhibit strong reasoning abilities, but their high computational costs limit their practical deployment. Recent studies reveal significant redundancy i…
dots.ocr: Multilingual Document Layout Parsing in a Single Vision-Language Model
Yumeng Li, Guang Yang, Hao Liu +2
Document Layout Parsing serves as a critical gateway for Artificial Intelligence (AI) to access and interpret the world's vast stores of structured knowledge. This process,which en…
Self-Questioning Language Models
Lili Chen, Mihir Prabhudesai, Katerina Fragkiadaki +2
Can large language models improve without external data -- by generating their own questions and answers? We hypothesize that a pre-trained language model can improve its reasoning…
Maximizing Confidence Alone Improves Reasoning
Mihir Prabhudesai, Lili Chen, Alex Ippoliti +3
Reinforcement learning (RL) has enabled machine learning models to achieve significant advances in many fields. Most recently, RL has empowered frontier language models to solve ch…
Employee Turnover Prediction: A Cross-component Attention Transformer with Consideration of Competitor Influence and Contagious Effect
Hao Liu, Yong Ge
Employee turnover refers to an individual's termination of employment from the current organization. It is one of the most persistent challenges for firms, especially those ones in…
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141
Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
Yizhe Huang, Xingbo Wang, Hao Liu +7
Traditional interactive environments limit agents' intelligence growth with fixed tasks. Recently, single-agent environments address this by generating new tasks based on agent act…
Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback
Kyuyoung Kim, Ah Jeong Seo, Hao Liu +2
Large language models (LLMs) fine-tuned with alignment techniques, such as reinforcement learning from human feedback, have been instrumental in developing some of the most capable…
CriticBench: Benchmarking LLMs for Critique-Correct Reasoning
Zicheng Lin, Zhibin Gou, Tian Liang +3
The ability of Large Language Models (LLMs) to critique and refine their reasoning is crucial for their application in evaluation, feedback provision, and self-improvement. This pa…
ChipNeMo: Domain-Adapted LLMs for Chip Design
Mingjie Liu, Teodor-Dumitru Ene, Robert Kirby +39
ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we…
Quantifying the Variability Collapse of Neural Networks
Jing Xu, Haoxiong Liu
Recent studies empirically demonstrate the positive relationship between the transferability of neural networks and the within-class variation of the last layer features. The recen…