…However, training such agents is currently bottlenecked by a reliance on scraped external repositories, which limits domain diversity, environment controllability, and the targeting of specific capability deficits. We introduce LiteCoder-Terminal-Gen…
…However, standard OPD faces two coupled limitations. First, it requires direct access to the teacher's token-level logits, excluding a broad class of capable proprietary models from serving as teachers. Second…
…On-device deployment is in turn constrained by limited computation and memory. No single endpoint can deliver high-quality service across this spectrum. This article focuses on collaborative intelligence , a paradigm in…
…unified models have demonstrated strong capability in instruction-grounded video synthesis , but integrating a large high-fidelity generator into the unified training loop is computationally prohibitive, limiting achievable visual quality. We therefore…
…when sequential updates enable capability transfer and when they cause catastrophic forgetting . Existing methods mitigate forgetting through sequential fine-tuning , replay, regularization, or model merging , but offer limited criteria for determining when…
…AI-generated summary Large Language Models are being increasingly deployed as the decision-making core of autonomous agents capable of effecting change in external environments. Yet, in conversational benchmarks, which simulate real…
…that addresses limitations of existing datasets by providing contamination-limited, multitask evaluation across text-to-code, code-to-text, and code-to-code retrieval tasks with fine-tuned reranking capabilities. AI-generated…
…AI-generated summary Large language model agents increasingly rely on external skills to solve complex tasks, where skills act as modular units that extend their capabilities beyond what parametric memory alone supports…
…As a result, IR models trained on these datasets show limited generalization in real-world scenarios. In this work, we propose Generative Ground Truth (GGT) by using generative multimodal foundation models (MFMs…
…under incomplete information and limited temporal context of the underlying patient state, and may therefore be suboptimal, making it diff icu lt to assess the true reasoning capabilities of AI systems. We…