LLM-native advertising embeds sponsored content directly into model-generated responses, shifting the unit of sale from a fixed slot to a moment within an evolving conversation. Existing LLM ad-auction mechanisms primarily operate within a single response, settling the winner but not the timing. The extension is nontri...
Yan Fang, Jialin Chen, Chun Gan et al.· 0 citations
A novel annotation process for AII is contributed that accounts for a perceiver's own interpretative tendencies and quantitative and qualitative analyses of intent narratives with respect to diversity, plausibility and grounding.
Zong-Huan Li, Litian Li, Arthur Mercier et al.· arXiv.org· 0 citations
Controlling combinations of personality-related tendencies is important for adapting large language models to diverse interaction needs. But successful single-trait steering does not establish how to construct interventions for joint targets, or whether existing trait directions adequately represent them. We introduce...
Liu Zai, Yumeng Wang, Junchen Fu et al.· 0 citations
Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromises the validity of backtests and causal inference in finance and the social sciences. Point-in-time language models--trained exclusively on text available up to each cale...
Bryan Kelly, Semyon Malamud, Johannes Schwab et al.· 0 citations
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Equitable renewable-energy planning is a sequential decision problem, but the decision variables available to a public planner differ sharply between mature and emerging economies. In the former the government largely builds generation, while in the latter it steers private investment through incentives and quotas. We...
Riya Kinnarkar, Mansur M. Arief, Yan Pratama Akhra et al.· 0 citations
Recommendation systems, from traditional multi-stage to recent unified generative architectures, face challenges in incorporating diverse contextual signals, such as trending topics, breaking news, cultural events, and cross-surface user activities, into their ranking pipelines. These systems are designed to consume st...
Thematic indexing -- the practice of assigning structured conceptual labels to sections of text -- is essential to scholarly access in large-scale literary and historical editions, yet it remains a largely manual, labour-intensive process. This paper explores the application of machine learning to automatic thematic in...
Miguel Arana-Catania, Gillian Pink, Glenn Roe· 0 citations
Phone segmentation and recognition are inherently related tasks, yet modern approaches typically model them separately. We argue that phonetic structure is already latent in the representations of self-supervised speech models (S3Ms), so one only needs to steer them to solve both tasks. We leverage S3M-based Phonologic...
Shikhar Bharadwaj, Kwanghee Choi, Stephen McIntosh et al.· 0 citations
Large Audio-Language Models (LALMs) reason fluently about sound yet struggle to localize precisely when events occur, while classical Sound Event Detection (SED) attains frame-level precision only over a closed label set. At the intersection of these paradigms lies the task of Open-Vocabulary Audio Event Grounding: pre...
Zihan Zhang, Xize Cheng, Wenhao Yan et al.· 0 citations
Automated research agents increasingly generate code, retrieve literature, and draft scientific artifacts, but they often fail to verify whether generated experiments execute correctly or whether cited sources support generated claims. We present AutoResearch, an execution-grounded multi-agent framework for reliable re...
Rajesh Kumar, Waqar Ali, Junaid Ahmed et al.· 0 citations
Language models learn continuous programs over discrete symbols, with the embedding table and LM-head acting as the read/write interface between them. We show that this interface has gradient geometry distinct from dense hidden weights which can be exploited to improve the Pareto frontier across supervised finetuning,...
Any-angle path planning extends traditional graph-based path planning by allowing movement between any pair of vertices, rather than being restricted by predefined edges. It can find straighter and shorter paths in continuous space with graphs, making it particularly suitable for navigation in open areas. Many any-angl...
