Speech synthesis technology has made notable strides, yet challenges remain in delivering real-time, natural-sounding audio. Common obstacles include latency, pronunciation accuracy, and speaker consistency—issues that become critical in streaming applications where responsiveness is paramount. Additionally, handling complex linguistic inputs, such as tongue twisters or polyphonic words, often exceeds the capabilities of existing models. To address… →

One of the crucial factors in achieving high-quality outputs from these models lies in the design of prompts—carefully crafted input instructions that guide the model to produce the desired responses. Despite their importance, prompt creation is a labor-intensive process that often requires domain-specific knowledge and significant human effort. These limitations have spurred the development of… →

Long-context LLMs enable advanced applications such as repository-level code analysis, long-document question-answering, and many-shot in-context learning by supporting extended context windows ranging from 128K to 10M tokens. However, these capabilities come with computational efficiency and memory usage challenges during inference. Optimizations that leverage the Key-Value (KV) cache have emerged to address these issues, focusing on… →

Recently, AI agents have demonstrated very promising developments in automating mathematical theorem proving and code correctness verification using tools like Lean. Such tools pair code with specifications and proofs to ensure it meets its intended requirements, offering very strong safeguards in safety-critical applications. Artificial Intelligence has demonstrated that it can enable the fundamental steps of… →