Text understanding and language tasks
From the Macintosh to the iPhone to the iMac to the iPod, it’s hard to pick a best Apple product ever. But we tried to do so anyway.
Been thinking about this and want to know if others have hit the same issue. The dominant approach for agent memory (Mem0, Zep, most RAG ...
![[2601.11016] Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2601.11016: Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interp...
Lean Finder is a semantic search engine designed for the Lean programming language and mathlib, improving theorem retrieval by understand...
The paper presents NAViS, a novel model for node affinity prediction in temporal graphs, addressing challenges in current methods and out...
The paper introduces a new dimensionless data-quality parameter for language model pretraining, establishing a quality-aware scaling law ...
The paper introduces KVComm, a novel framework for efficient communication between Large Language Models (LLMs) using selective KV pair s...
Voxtral Realtime presents a novel streaming automatic speech recognition model achieving offline transcription quality with sub-second la...
The paper presents Neurosymbolic Retrievers for Retrieval-augmented Generation, addressing the limitations of traditional RAG systems by ...
This article introduces Conflict-Aware Fusion, a framework designed to address Logic Inertia in large language models (LLMs) by integrati...
This article presents a novel approach to psychiatric comorbidity through the creation of a large-scale dataset and a multi-agent diagnos...
This article evaluates 25 pretrained molecular embedding models for molecular representation learning, revealing that most show little im...
This article presents a novel approach to predicting the virality of memes on Reddit using a multimodal dataset and advanced machine lear...
The paper presents VIRTUE, a novel Visual-Interactive Text-Image Universal Embedder that enhances multimodal representation learning by i...
The paper presents JEF-Hinter, a system designed to enhance the adaptation of web agents by leveraging offline knowledge, improving perfo...
This paper introduces a novel framework for Graph Neural Networks (GNNs) that utilizes a one-hot graph encoder embedding (GEE) to enhance...
The paper presents E-BATS, a novel framework for efficient backpropagation-free test-time adaptation (TTA) tailored for speech foundation...
This paper presents a theoretical framework for Top-$k$ decoding in language models, explaining its efficiency and generalizing its appli...
The paper presents SuperMAN, a framework designed for learning from temporally sparse and heterogeneous data, enhancing interpretability ...
FairSHAP introduces a novel preprocessing framework that utilizes Shapley value attribution to enhance fairness in machine learning model...
The paper presents FedSDAF, a novel framework that enhances Federated Domain Generalization by leveraging source domain awareness, demons...
GraphOmni introduces a benchmark framework for evaluating large language models on graph-theoretic tasks, highlighting performance variab...
The paper presents AgentOptics, an AI framework for autonomous control of optical systems, achieving high task success rates and demonstr...
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