Large Language Models (LLMs) face significant scalability limitations in improving their reasoning capabilities through data-driven imitation, as better performance demands exponentially more high-quality training examples. Exploration-based methods, particularly reinforcement learning (RL), offer a promising alternative to overcome these limitations. The transformation from data-driven to exploration-based approaches presents two key challenges: developing efficient methods to generate…
Artificial intelligence (AI) has made significant strides in developing language models capable of solving complex problems. However, applying these models to real-world scientific challenges remains difficult. Many AI agents struggle with tasks requiring multiple cycles of observation, reasoning, and action. Moreover, existing models often lack the ability to integrate tools effectively or maintain consistency in…
Software engineering agents have become essential for managing complex coding tasks, particularly in large repositories. These agents employ advanced language models to interpret natural language descriptions, analyze codebases, and implement modifications. Their applications include debugging, feature development, and optimization. The effectiveness of these systems relies on their ability to handle real-world challenges, such as interacting…
Appropriateness refers to the context-specific standards that guide behavior, speech, and actions in various social settings. Humans naturally navigate these norms, acting differently based on whether they are among friends, family, or a professional environment. Similarly, AI systems must adapt their behavior to fit the context, as the standards for a comedy-writing assistant differ from…
Large Language Models (LLMs) have revolutionized text generation capabilities, but they face the critical challenge of hallucination, generating factually incorrect information, particularly in long-form content. Researchers have developed Retrieved-Augmented Generation (RAG) to address this issue, which enhances factual accuracy by incorporating relevant documents from reliable sources into the input prompt. While RAG has shown promise,…
Designing GUI agents that perform human-like tasks on graphical user interfaces faces a critical obstacle: collecting high-quality trajectory data for training. Existing methods depend on expensive and time-consuming human supervision or on generating synthetic data, which can hardly reflect the diversity and dynamics in the real world. Those constraints significantly limit the GUI agents’ scalability…
Power distribution systems are often conceptualized as optimization models. While optimizing agents to perform tasks works well for systems with limited checkpoints, things begin to go out of hand when heuristics tackle multiple tasks and agents. Scaling dramatically increases the complexity of assignment problems, often NP-hard and nonlinear. Optimization methods become the white elephants in…
The development of large language models (LLMs) has significantly advanced artificial intelligence (AI) across various fields. Among these advancements, mobile GUI agents—designed to perform tasks autonomously on smartphones—show considerable potential. However, evaluating these agents poses notable challenges. Current datasets and benchmarks often rely on static frame evaluations, which provide snapshots of app interfaces for agents…
Evaluating the real-world applicability of large language models (LLMs) is essential to guide their integration into practical use cases. One key challenge in assessing LLMs is their tendency to exploit fixed datasets during testing, leading to inflated performance metrics. Static evaluation frameworks often fail to determine a model’s ability to adapt to feedback or provide…
Proteins, the essential molecular machinery of life, play a central role in numerous biological processes. Decoding their intricate sequence, structure, and function (SSF) is a fundamental pursuit in biochemistry, molecular biology, and drug development. Understanding the interplay between these three aspects is crucial for uncovering the principles of life at a molecular level. Computational tools…