Academic
arXiv:2602.16220v1 Announce Type: new Abstract: Modeling multiscale patterns is crucial for long-term time series forecasting (TSF). However, redundancy and noise in time series, together with …
arXiv:2602.16224v1 Announce Type: new Abstract: Time series data are prone to noise in various domains, and training samples may contain low-predictability patterns that deviate from …
arXiv:2602.16229v1 Announce Type: new Abstract: Learning latent actions from action-free video has emerged as a powerful paradigm for scaling up controllable world model learning. Latent …
arXiv:2602.16236v1 Announce Type: new Abstract: We revisit the classical problem of universal prediction of stochastic sequences with a finite time horizon $T$ known to the …
arXiv:2602.16274v1 Announce Type: new Abstract: We present the first high-probability regret bound for classical online Q-learning in infinite-horizon discounted Markov decision processes, without relying on …
arXiv:2602.16284v1 Announce Type: new Abstract: Scaling language models to long contexts is often bottlenecked by the size of the key-value (KV) cache. In deployed settings, …
arXiv:2602.15757v1 Announce Type: new Abstract: Online sexism appears in various forms, which makes its detection challenging. Although automated tools can enhance the identification of sexist …
arXiv:2602.15758v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) perform strongly on single-turn chart generation, their ability to support real-world exploratory data analysis …
arXiv:2602.15769v1 Announce Type: new Abstract: Multimodal Large Language Models (mLLMs) are often used to answer questions in structured data such as tables in Markdown, JSON, …
arXiv:2602.15778v1 Announce Type: new Abstract: Evaluating the quality of automatically generated text often relies on LLM-as-a-judge (LLM-judge) methods. While effective, these approaches are computationally expensive …
arXiv:2602.15183v1 Announce Type: cross Abstract: Vision Language Models (VLMs) are designed to extend Large Language Models (LLMs) with visual capabilities, yet in this work we …
