arXiv:2511.11583v1 Announce Type: new Abstract: Large language models (LLMs) show promise for personalized financial recommendations but are hampered by context limits, hallucinations, and a lack of behavioral grounding. Our prior work, FLARKO, embedded structured knowledge graphs (KGs) in LLM prompts…
arXiv:2511.11579v1 Announce Type: new Abstract: An important aspect subtending language understanding and production is the ability to independently encode positional and symbolic information of the words within a sentence. In Transformers, positional information is typically encoded using Positional Encodings (PEs).…
MIT researchers developed a way to identify the smallest dataset that guarantees optimal solutions to complex problems.
arXiv:2504.18720v2 Announce Type: replace Abstract: Deep learning has advanced weather forecasting, but accurate predictions first require identifying the current state of the atmosphere from observational data. In this work, we introduce Appa, a score-based data assimilation model generating global atmospheric…
arXiv:2511.13503v1 Announce Type: cross Abstract: Modern business and economic datasets often exhibit nonlinear, multi-scale structures that traditional linear tools under-represent. Topological Data Analysis (TDA) offers a geometric lens for uncovering robust patterns, such as connected components, loops and voids, across…
arXiv:2410.01623v3 Announce Type: replace Abstract: Low-rank training has emerged as a promising approach for reducing memory usage in training Large Language Models (LLMs). Previous methods either rely on decomposing weight matrices (e.g., LoRA), or seek to decompose gradient matrices (e.g.,…
arXiv:2511.12394v1 Announce Type: cross Abstract: We propose a new representation learning solution for the classification of cognitive load based on Electroencephalogram (EEG). Our method integrates both time and frequency domains by first passing the raw EEG signals through the convolutional…
IBM recently announced the Granite 4.0 family of small language models. The model family aims to deliver faster speeds and significantly lower operational costs at acceptable accuracy vs. larger models. Granite 4.0 features a new hybrid Mamba/transformer architecture that largely…
IBM recently announced the Granite 4.0 family of small language models. The model family aims to deliver faster speeds and significantly lower operational costs at acceptable accuracy vs. larger models. Granite 4.0 features a new hybrid Mamba/transformer architecture that largely…
IBM recently announced the Granite 4.0 family of small language models. The model family aims to deliver faster speeds and significantly lower operational costs at acceptable accuracy vs. larger models. Granite 4.0 features a new hybrid Mamba/transformer architecture that largely…
