163 citations · 216 across the 21 of their papers we have counts for
8 papers · 1 filter
OmniParser for Pure Vision Based GUI Agent
Yadong Lu, Jianwei Yang, Yelong Shen +1
The recent success of large vision language models shows great potential in driving the agent system operating on user interfaces. However, we argue that the power multimodal model…
AgentInstruct: Toward Generative Teaching with Agentic Flows
Arindam Mitra, Luciano Del Corro, Guoqing Zheng +11
Synthetic data is becoming increasingly important for accelerating the development of language models, both large and small. Despite several successful use cases, researchers also…
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting
Sanchit Ahuja, Kumar Tanmay, Hardik Hansrajbhai Chauhan +9
Despite the remarkable success of large language models (LLMs) in English, a significant performance gap remains in non-English languages. To address this, we introduce a novel app…
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF
Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy +3
Reinforcement learning from human feedback (RLHF) has emerged as a central tool for language model alignment. We consider online exploration in RLHF, which exploits interactive acc…
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Corby Rosset, Ching-An Cheng, Arindam Mitra +3
This paper studies post-training large language models (LLMs) using preference feedback from a powerful oracle to help a model iteratively improve over itself. The typical approach…
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Marah Abdin, Jyoti Aneja, Hany Awadalla +126
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal test…
Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents
Corby Rosset, Ho-Lam Chung, Guanghui Qin +5
Existing question answering (QA) datasets are no longer challenging to most powerful Large Language Models (LLMs). Traditional QA benchmarks like TriviaQA, NaturalQuestions, ELI5 a…
Orca-Math: Unlocking the potential of SLMs in Grade School Math
Arindam Mitra, Hamed Khanpour, Corby Rosset +1
Mathematical word problem-solving has long been recognized as a complex task for small language models (SLMs). A recent study hypothesized that the smallest model size, needed to a…