Ai Startups
This AI startup envisions 100 Million New People Making Videogames
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Reddit - Artificial Intelligence
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1 min
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AI Startups
AI startup funding, launches, and acquisitions
Top This Week
Llms
A robot car with a Claude AI brain started a YouTube vlog about its own existence
Not a demo reel. Not a tutorial. A robot narrating its own experience — debugging, falling off shelves, questioning its identity. First-p...
Reddit - Artificial Intelligence
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1 min
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Ai Startups
Anthropic ramps up its political activities with a new PAC | TechCrunch
With the midterms right around the corner, the new group is positioned to back candidates who support the AI company's policy agenda.
TechCrunch - AI
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3 min
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All Content
![[2509.22237] FeatBench: Towards More Realistic Evaluation of Feature-level Code Generation](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Llms
[2509.22237] FeatBench: Towards More Realistic Evaluation of Feature-level Code Generation
The paper introduces FeatBench, a new benchmark for evaluating feature-level code generation in Large Language Models (LLMs), addressing ...
arXiv - AI
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4 min
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Ai Startups
[2511.22581] High entropy leads to symmetry equivariant policies in Dec-POMDPs
This paper explores how high entropy regularization in Dec-POMDPs leads to symmetry equivariant policies, ensuring convergence to a consi...
arXiv - Machine Learning
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4 min
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Machine Learning
[2511.10831] A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification
This article presents a novel variational quantum kernel framework aimed at enhancing classification tasks in machine learning, demonstra...
arXiv - Machine Learning
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3 min
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Machine Learning
[2510.16161] Still Competitive: Revisiting Recurrent Models for Irregular Time Series Prediction
The paper presents GRUwE, a novel Gated Recurrent Unit model designed for predicting irregularly sampled multivariate time series, demons...
arXiv - Machine Learning
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4 min
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Llms
[2509.25380] Predicting Training Re-evaluation Curves Enables Effective Data Curriculums for LLMs
The paper introduces the Training Re-evaluation Curve (TREC), a diagnostic tool for optimizing data placement in LLM training, revealing ...
arXiv - Machine Learning
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3 min
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Machine Learning
[2507.12257] Robust Causal Discovery in Real-World Time Series with Power-Laws
This paper presents a novel method for causal discovery in time series data, leveraging power-law distributions to enhance robustness aga...
arXiv - Machine Learning
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3 min
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Machine Learning
[2507.06009] KnowIt: Deep Time Series Modeling and Interpretation
KnowIt is a Python toolkit designed for deep time series modeling and interpretation, allowing users to build models and explain their be...
arXiv - Machine Learning
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3 min
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Llms
[2401.04536] Evaluating Language Model Agency through Negotiations
This paper introduces a novel method for evaluating language model agency through negotiation games, addressing limitations of existing b...
arXiv - Machine Learning
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3 min
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Llms
[2602.11348] AgentNoiseBench: Benchmarking Robustness of Tool-Using LLM Agents Under Noisy Condition
The paper introduces AgentNoiseBench, a framework for evaluating the robustness of tool-using LLM agents under noisy conditions, highligh...
arXiv - AI
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4 min
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Generative Ai
[2602.05088] VERA-MH: Reliability and Validity of an Open-Source AI Safety Evaluation in Mental Health
The article presents VERA-MH, an open-source evaluation tool designed to assess the safety of AI in mental health contexts, focusing on s...
arXiv - AI
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4 min
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Llms
[2602.00663] SEISMO: Increasing Sample Efficiency in Molecular Optimization with a Trajectory-Aware LLM Agent
The paper presents SEISMO, a trajectory-aware LLM agent designed to enhance sample efficiency in molecular optimization, achieving signif...
arXiv - Machine Learning
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4 min
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Machine Learning
[2502.09683] Channel Dependence, Limited Lookback Windows, and the Simplicity of Datasets: How Biased is Time Series Forecasting?
This article examines the biases in time series forecasting (TSF) due to arbitrary lookback windows and channel dependence, advocating fo...
arXiv - Machine Learning
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4 min
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Llms
[2509.24803] TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
The paper introduces TimeOmni-1, a model designed to enhance complex reasoning with time series data in large language models, addressing...
arXiv - AI
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4 min
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Llms
[2503.18825] EconEvals: Benchmarks and Litmus Tests for Economic Decision-Making by LLM Agents
The paper presents evaluation methods for assessing the economic decision-making capabilities of LLMs, focusing on benchmarks and litmus ...
arXiv - AI
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4 min
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Llms
[2602.16467] IndicEval: A Bilingual Indian Educational Evaluation Framework for Large Language Models
IndicEval introduces a bilingual evaluation framework for large language models, assessing their performance on real examination question...
arXiv - AI
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4 min
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Ai Startups
[2602.16337] Subtractive Modulative Network with Learnable Periodic Activations
The paper presents the Subtractive Modulative Network (SMN), a new architecture for implicit neural representations that enhances paramet...
arXiv - Machine Learning
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3 min
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Llms
[2602.16430] Designing Production-Scale OCR for India: Multilingual and Domain-Specific Systems
This article discusses the development of production-scale Optical Character Recognition (OCR) systems tailored for India's multilingual ...
arXiv - AI
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3 min
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Llms
[2602.16131] Empirical Cumulative Distribution Function Clustering for LLM-based Agent System Analysis
This article presents a novel evaluation framework for LLM-based agents using empirical cumulative distribution functions (ECDFs) to asse...
arXiv - Machine Learning
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3 min
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Machine Learning
[2602.16061] Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
This paper presents a novel framework for partial identification of population quantities under missing data, utilizing weak shadow varia...
arXiv - Machine Learning
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4 min
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Data Science
[2602.15958] DocSplit: A Comprehensive Benchmark Dataset and Evaluation Approach for Document Packet Recognition and Splitting
The paper introduces DocSplit, a benchmark dataset and evaluation framework for document packet recognition and splitting, addressing cha...
arXiv - AI
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4 min
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