Patent search requires processing documents routinely exceeding tens of thousands of tokens. Most neural retrieval approaches operate on truncated inputs, limiting their effectiveness. Graph-based retrieval addresses this by representing each patent as a structured invention graph, but constructing these graphs relies...
Nikolai Zenovkin, Sebastian Bj\"orkqvist· 0 citations
LLM agents with tool-calling capabilities can access external services and private user data, but they may retrieve more information than a user's request explicitly requires. We study this behavior in structured tool-calling agents and term it proactive over-authorization. This setting differs from filesystem-level co...
Tao-Lin Zhang, Jiu-Heng Wan, Han-Yu Wang et al.· 0 citations
Q-SPT is proposed, a low-frame-rate dual-stream speech tokenizer with separate, context-aware, learnable query-based compressors specialized for semantic and acoustic representations that yields the best speech recognition accuracy and text-to-speech perceptual quality with competitive intelligibility.
This work forms utterance-level CS-LID as multi-label language-set prediction and proposes a set generator that directly outputs the languages in an utterance, comparing it against atomic-pair and score-based classification baselines.
Shunsuke Mitsumori, Matthew Wiesner, S. Morishima et al.· 0 citations
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Semantic IDs (SIDs) compress item embeddings into discrete code sequences used in generative retrieval. We ask whether a multilingual encoder is sufficient for different-language renderings of the same product to receive language-consistent SIDs. Using Amazon ESCI listings rendered in English, Spanish, and Japanese, we...
AuraForge is introduced to synthesize and validate executable security tests for training secure coding agents, and it is demonstrated that AuraForge provides more diverse and reliable security supervision to train secure coding agents.
Dan-Qing Wang, Song-Wen Zhao, Harsh Sharma et al.· 0 citations
Vision-Language Models (VLMs) enable video annotation at scale, but costs accumulate quickly: processing a typical 60-second short-form video at one frame per second requires millions of tokens. To reduce costs, researchers rely on heuristics such as sampling a subset of frames, compressing videos into image grids, or...
A review of indexed contributions from 2007 to 2026 finds that platform mentions shift from blogs toward Twitter and, more recently, Reddit, and how AI-mediated interactions complicate these questions is discussed.
We study commercial intent inference that runs entirely on the user's device, under three constraints frozen before the work began: the downloaded payload under 3 MiB, Tier-0 inference under 20 ms at p95, and no raw text, content embedding, or stable identifier leaving the device. Under them we build a retrieval path o...
Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with consistent characters and aligned audio remains challenging. Existing methods often suffer from narrative drift, unstable character identity, weak cross-scene continuity, a...
Ting Huang, Biao Wu, Rong-Hao Chen et al.· 0 citations
While Electronic Health Records (EHRs) offer a wealth of clinical data, effectively augmenting a patient's records with heterogeneous external knowledge to predict the patient's clinical risk remains a significant challenge. Existing methods fail to capture disease severity, treatment responses, and nuanced clinical pr...
Kyunghoon Jeon, Youmin Ko, Woohwan Jung et al.· 0 citations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.