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3,445 papers
This work constructs a signal by force-decoding a fixed set of candidate answers and develops a framework that manipulates the image and question text separately, making the boundary searchable for any behaviour formulated as a choice between candidate answers.
Abstract interpretation provides a generic framework to design static analysis, and has been widely applied in analysis of real-world programs. The scalability and precision of these analyses depend largely on the chosen abstract domain. The template polyhedra domain is well-known for offering a compelling trade-off be...
Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-aware video captioning and person-centric question answering that combines automatic character identification, explicit spatial grounding, and task-specific adaptation. St...
COBOL remains one of the most widely deployed programming languages in mission-critical business systems, yet the pool of developers who can maintain it is shrinking. Automated translation to modern languages like Java is an increasingly attractive modernisation strategy, but systematic evaluation of available approach...
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Current frontier LLMs leverage vast training datasets with knowledge about a broad range of programming languages and frameworks, and can often solve tasks with minimal prompting. However, there are scenarios where remote LLMs are unsuitable, due to cost, privacy, security, or intellectual property concerns, and local...
Determining whether a test execution should pass or fail remains a core obstacle to end-to-end test automation. Recent work has focused mainly on generating assertions from source context, leav- ing open how much pass/fail signal can be recovered directly from runtime behavior, especially under subject transfer. We pre...
This work contributes a phonetically- and gender-balanced two-tier Bangladeshi Bangla corpus balanced via a tiered Jensen-Shannon divergence objective over conjunct clusters (juktakkhor), together with three fine-tuning changes: a merge-consistent tokenizer extension, Bangla text normalization, and a prompt-masked dual...
A theory built on two quantities of the image interface: S, the number of visual tokens across an object's side, and L, the content a call must cover, which concludes that recognition improves gradually with S, and any search strategy, zoom agents included, obeys a recall-cost frontier.
Goldsmith, an agentic pipeline that turns a small gold set---expert-annotated calibration examples representing the intended task boundaries---into a reusable structured annotation definition, shows that scarce expert supervision can support both task-definition learning and scalable annotation.
Embedding tables are among the largest components of modern language models. Most compression methods fix a coding geometry such as coordinate blocks, low-rank subspaces, or unrestricted codebooks, and optimize within it. We instead ask whether the coding geometry can itself be discovered. We introduce \emph{OrBIT}, a...
Adaptive computation aims to improve language-model inference by tailoring execution to each input. For layer programs, oracle evaluations use known answers to estimate the potential gain from this flexibility, before a practical selector is available. However, a gain from selection does not by itself explain why the c...
We argue that pattern recognition and step-by-step reasoning are two ends of a spectrum. A large language model (LLM) learns to reason step-by-step when data is structured such that the next token depends on a small amount of preceding context. Inference in LLMs resembles pattern recognition when the next token depends...
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