AI startup funding, launches, and acquisitions
On the latest episode of TechCrunch’s Equity podcast, we debated Elon Musk's vision for data centers in space.
I've received 3 out of 4 acknowledgements, All of them basically are choosing Option A without changing their scores, because their initi...
With an eye towards the evolving business landscape, the Carl H. Lindner College of Business is meeting the moment with the introduction ...
![[2406.14045] LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The LTSM-Bundle introduces a comprehensive toolbox and benchmark for training Large Time Series Models (LTSMs), enhancing time series for...
The paper introduces Cross-Attention Token Pruning (CATP), a method designed to enhance the accuracy of multimodal models by effectively ...
FiMI is a domain-specific language model tailored for the Indian finance ecosystem, enhancing digital payment systems with improved perfo...
The paper discusses the need for a verification-first approach in AI-assisted peer review to prevent the collapse of the review process, ...
This article explores the security implications of agentic AI systems, detailing specific threats, defense strategies, and evaluation met...
The paper presents RLIE, a framework that integrates large language models (LLMs) with probabilistic rule learning to enhance rule genera...
The paper presents SCOPE, a framework for selective pairwise evaluation using large language models (LLMs) that improves judgment accurac...
The paper explores EXCODER, a method for explainable classification of discrete time series representations, enhancing interpretability w...
The paper presents RADAR, a novel evaluation framework for Multi-modal Large Language Models (MLLMs) that addresses performance bottlenec...
The paper introduces SQuTR, a new benchmark for evaluating the robustness of spoken query retrieval systems under various acoustic noise ...
The paper presents ALOE, an action-level off-policy evaluation framework aimed at enhancing vision-language-action models through reinfor...
This article evaluates HiFloat formats for low-bit inference on Ascend NPUs, highlighting their efficiency and compatibility with state-o...
The paper presents Power Interpretable Causal ODE Networks (PICODE), a novel model for explainable anomaly detection and root cause analy...
The paper presents Bench-MFG, a benchmark suite designed to standardize evaluations in learning for stationary Mean Field Games, addressi...
The paper introduces RankLLM, a framework for evaluating large language models (LLMs) by quantifying question difficulty, enhancing model...
The paper presents Policy4OOD, a knowledge-guided world model designed to simulate policy interventions against the opioid overdose crisi...
BrowseComp-$V^3$ introduces a new benchmark for evaluating multimodal browsing agents, focusing on complex reasoning across visual and te...
This paper explores the integration of AI agents, particularly large language models (LLMs), with traditional operations research (OR) me...
This paper presents a scalable pipeline for generating high-quality training data for web agents, introducing a novel evaluation framewor...
The article discusses three official reviews of ACL ARR Jan 2026, presenting average scores for Overall Assessment and Confidence, prompt...
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