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November 20, 20254 min readA new evaluation pipeline called FiSCo uncovers hidden biases and offers an assessment framework that evolves alongside language models.
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September 2, 20253 min read
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Featured news
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2025Fine-tuning large language models (LLMs) with a collection of large and diverse instructions has improved the model’s generalization to different tasks, even for unseen tasks. However, most existing instruction datasets include only single instructions, and they struggle to follow complex instructions composed of multiple subtasks. In this work, we propose a novel concept of compositional instructions called
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2025Recent advancements in language-guided diffusion models for image editing are often bottle-necked by cumbersome prompt engineering to precisely articulate desired changes. An intuitive alternative calls on guidance from in-the-wild image exemplars to help users bring their imagined edits to life. Contemporary exemplar-based editing methods shy away from leveraging the rich latent space learnt by pre-existing
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2025One common approach for question answering over speech data is to first transcribe speech using automatic speech recognition (ASR) and then employ text-based retrieval-augmented generation (RAG) on the transcriptions. While this cascaded pipeline has proven effective in many practical settings, ASR errors can propagate to the retrieval and generation steps. To overcome this limitation, we introduce SpeechRAG
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ICSE 20252025Pricing agreements at AWS define how customers are billed for usage of services and resources. A pricing agreement consists of a complex sequence of terms that can include free tiers, savings plans, credits, volume discounts, and other similar features. To ensure that pricing agreements reflect the customers’ intentions, we employ a protocol that runs a set of validations that check all pricing agreements
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2025Following the great progress in text-conditioned image generation there is a dire need for establishing clear comparison benchmarks. Unfortunately, assessing performance of such models is highly subjective and notoriously difficult. Current automatic assessment of generated images quality and their alignment to text are approximate at best while human assessment is subjective, poorly calibrated and not
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