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Human reviewers or LLMs are often the only options for evaluating free-form material. However, their evaluation can be inaccurate and the process is time-consuming, costly, and arduous. The relief from this manual work comes with prompt engineering or the development of a unique optimization procedure, which is necessary for LLM evaluations to function as intended.…
Optimal transport is a mathematical discipline focused on determining the most efficient way to move mass between probability distributions. This field has wide-ranging applications in economics, where it is used to model resource allocation; in physics, to simulate particle dynamics; and in machine learning, where it aids in data alignment and analysis. By solving transportation…
Together AI has unveiled a groundbreaking advancement in AI inference with its new inference stack. This stack, which boasts a decoding throughput four times faster than the open-source vLLM, surpasses leading commercial solutions like Amazon Bedrock, Azure AI, Fireworks, and Octo AI by 1.3x to 2.5x. The Together Inference Engine, capable of processing over 400…
Conversational AI systems like ChatGPT have gained considerable attention among the various AI advancements. These systems utilize advanced machine learning algorithms and natural language processing to assist users in numerous tasks, such as drafting emails, conducting research, and providing detailed information. The proliferation of such AI tools significantly transforms how office tasks are executed, contributing…
Instruction-tuned LLMs can handle various tasks using natural language instructions, but their performance is sensitive to how instructions are phrased. This issue is critical in healthcare, where clinicians, who may need to be more skilled, prompt engineers, need reliable outputs. The robustness of LLMs to variations in clinical task instructions is thus questioned. Despite advancements…
Traditional methods, relying solely on formal proof data, overlook valuable informal reasoning processes crucial to human mathematicians. The absence of natural language thought processes in formal proofs creates a significant gap between human reasoning and machine-driven proofs. Existing language models specialized for generating tactics in formal mathematics often fail to leverage the benefits of thought…
Recently, diffusion models have become powerful tools in various fields, like image and 3D object generation. Their success comes from their ability to handle denoising tasks with different types of noise, efficiently turning random noise into the target data distribution through repeated denoising steps. Using Transformer-based structures, it has been shown that adding more parameters…
Large language models (LLMs) demonstrate proficiency in information retrieval and creative writing, with notable improvements in mathematics and coding. ZebraLogic, a benchmark consisting of Logic Grid Puzzles, assesses LLMs’ logical reasoning capabilities. Each puzzle presents N houses with M features, requiring unique value assignments based on given clues. This task, a Constraint Satisfaction Problem (CSP),…
DeepSeek has recently released its latest open-source model on Hugging Facel, DeepSeek-V2-Chat-0628. This release marks a significant advancement in AI-driven text generation and chatbot technology capabilities, positioning DeepSeek at the forefront of the industry. DeepSeek-V2-Chat-0628 is an enhanced iteration of the previous DeepSeek-V2-Chat model. This new version has been meticulously refined to deliver superior performance…
Automating mathematical reasoning has long been a goal in artificial intelligence, with formal frameworks like Lean 4, Isabelle, and Coq playing a significant role. These frameworks enable users to write machine-verifiable proofs of mathematical theorems, providing a structured environment for proving complex problems. Developing neural theorem-provers, which aim to automate this process, requires rigorous benchmarks…