Preprint2026
Beyond IID: How General Are Tabular Foundation Models, Really?
Unknown
This paper critically evaluates tabular foundation models, showing they excel on tiny datasets but fail to generalize beyond IID assumptions.
0Jun 1, 2026
arXiv
AI Research
AI & ML Research Papers
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114 papersPreprintarXiv.org2026
Benchmarking Agents on Hard CLI Tasks
Mike A. Merrill, Alexander G Shaw, Nicholas Carlini, et al.
Terminal-Bench 2.0 is a hard benchmark of 89 real-world-inspired CLI tasks where frontier agents score below 65%, with error analysis and public dataset/harness.
342Jan 17, 2026Benchmarks
arXiv
ConferenceIEEE Transactions on Pattern Analysis and Machine Intelligence2014
Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments
Catalin Ionescu, Dragos Papava, Vlad Olaru, et al.
Introduces Human3.6M, a large-scale dataset of 3.6 million accurate 3D human poses with synchronized images, motion capture, and depth data, along with statistical models and evaluation baselines for 3D human sensing.
4.0kJan 31, 2014Computer Vision
Preprint2026
HarmProfile: Characterizing Harmful Distributions in Frontier LLMs
Zhouyuan Ma, Yutao Wu, Hanxun Huang, et al.
HarmProfile is a content-centric benchmark dataset of over 80,000 validated harmful artifacts from 23 frontier LLMs, defining model-level risk profiles and revealing that harmfulness and diversity grow with model capability.
0Jun 11, 2026Large Language ModelsAlignment
arXiv
Preprint2026
Gaze Target Estimation Anywhere with Concepts
Xu Cao, Houze Yang, Vipin Gunda, et al.
Introduces Promptable Gaze Target Estimation (PGE), a concept-driven paradigm using text or visual prompts for end-to-end gaze analysis, with a new dataset Gaze-Co and model GazeAnywhere.
0Aug 11, 2026TransformersPrompting
arXiv
PreprintarXiv.org2024
AI benchmarks and datasets for LLM evaluation
Todor Ivanov, V. Penchev
This paper surveys AI benchmarks and datasets for evaluating large language models, providing a structured overview of existing resources and their applications.
10Dec 1, 2024Fine TuningBenchmarks
arXiv
PreprintDiagnostics2021
TransMed: Transformers Advance Multi-Modal Medical Image Classification
Yin Dai, Yifan Gao, Fayu Liu
TransMed combines CNN and transformer architectures for multi-modal medical image classification, achieving significant accuracy improvements on parotid gland and knee injury datasets.
467Jul 31, 2021TransformersPrompting
arXiv
PreprintComputational Visual Media2019
Salient object detection: A survey
Ali Borji, Ming-Ming Cheng, Qibin Hou, et al.
A comprehensive survey of salient object detection covering 228 publications, including roots, core techniques, datasets, evaluation metrics, and future directions.
839Jun 1, 2019Computer Vision
arXiv
PreprintDrug Discovery Today Technologies2020
A compact review of molecular property prediction with graph neural networks
Oliver Wieder, Stefan M. Kohlbacher, Mélaine A. Kuenemann, et al.
This review structures the dynamic field of GNNs for molecular property prediction by classifying 80 GNNs used across 20+ properties and 48 datasets.
552Dec 1, 2020Neural Networks
JournalDROPS (Schloss Dagstuhl – Leibniz Center for Informatics)2024
Analysis of Points of Interests Recommended for Leisure Walk Descriptions
Bajaj, Payal, Campos, Daniel, Craswell, Nick, et al.
This paper presents a dataset for the Advertisement in Retrieval-Augmented Generation task at Touché 2025, using segments from MS MARCO V2.1 and queries from Webis Generated Native Ads 2024.
1.3kOct 10, 2024Retrieval Augmented Generation
PreprintConference on Empirical Methods in Natural Language Processing2025
Protein LLMs
Yijia Xiao, Wanjia Zhao, Junkai Zhang, et al.
This paper provides the first comprehensive overview of Protein LLMs, covering architectures, training datasets, evaluation metrics, and applications, with a structured taxonomy from over 100 articles.
43Feb 21, 2025Large Language Models
arXiv
Preprint2026
Mitra: Mixed synthetic priors for enhancing tabular foundation models
Unknown
Mitra introduces mixed synthetic priors to enhance tabular foundation models, improving in-context learning performance across diverse tabular datasets.
0Jan 1, 2026In Context Learning
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