Researchers have proposed using complete cyclic subtask graphs to improve the performance of large language model (LLM) agents in long-horizon tool-us...
Researchers have found that fine-tuning language models for specific tasks can cause them to lose their ability to refuse harmful requests. This is a ...
Researchers have proposed a new method for on-policy distillation called Preference-Based Self-Distillation (PBSD). Unlike previous methods that rely ...
Researchers have developed GRALIS, a new method for explaining how deep neural networks make decisions. GRALIS combines two existing methods, coalitio...
Researchers have introduced a new AI architecture called S-AI-Recursive, which uses a bio-inspired approach to implement reasoning as a closed-loop it...
Researchers have developed a method for creating synthetic images of satellites that closely resemble real-world images while preserving important ann...
Researchers have proposed a new approach to reinforcement learning called Q-Value Expectile Disagreement (QED). The goal of QED is to reduce the varia...
Researchers have developed a metric called the Word Coverage Score (WCS) to measure how well large language models (LLMs) can generate diverse and uni...
Researchers have developed Chatterbox-Flash, a text-to-speech model that can generate speech without prior training data. The model uses a block-diffu...
Researchers have proposed an Audio Interaction Model that allows for continuous and interactive audio processing. Unlike current large language models...
Researchers have developed a new framework called INFUSER that improves the reasoning abilities of language models through self-evolution. The framewo...
Researchers Lezhi Tan and Tijana Zrnic propose a new approach to using synthetic data in scientific research. They argue that synthetic data can be bi...