mas
mask2former-swin-large-cityscapes-semanticbert-base-japanese-whole-word-maskingmask2former-swin-large-ade-semanticbert-large-uncased-whole-word-masking-squad2mask2former-swin-tiny-coco-instancebert-large-cased-whole-word-masking-finetuned-squadmask2former-swin-small-coco-instanceMASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_metric
Datasets
All datasets matching “mas”dataposteramazon_massive_intent
MassiveIntentClassification
An MTEB dataset
Massive Text Embedding Benchmark
MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages
Task category
t2c
Domains
Spoken
Reference
https://arxiv.org/abs/2204.08582
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["MassiveIntentClassification"])
evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/amazon_massive_intent.observation-masking-eval-logs
Eval Logs
Paper | Code
This repository contains model evaluation logs for four deep-research / web-agent benchmarks. Each run directory contains evaluated.jsonl judge results and node_0_shard_*.jsonl trajectory logs. Plot files and local bookkeeping files are intentionally excluded.
CM denotes the observation mask context management setting used in the paired run.
Data Access
You can download all released evaluation data, including tasks and… See the full description on the dataset page: https://huggingface.co/datasets/i-DeepSearch/observation-masking-eval-logs.MASIV
MASIV Multi-Sequence Dataset
Toward Material-Agnostic System Identification from Videos
ICCV 2025
Yizhou Zhao1, Haoyu Chen1, Chunjiang Liu1, Zhenyang Li2, Charles Herrmann3, Junhwa Hur3, Yinxiao Li3, Ming‑Hsuan Yang4, Bhiksha Raj1, Min Xu1*
1Carnegie Mellon University 2University of Alabama at Birmingham 3Google 4UC Merced
Introduction
The MASIV Multi-Sequence Dataset is a synthetic dataset generated by Genesis to evaluate the generalization of data-driven… See the full description on the dataset page: https://huggingface.co/datasets/yizhouz/MASIV.massive MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations
for the Natural Language Understanding tasks of intent prediction and slot annotation.
Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing
the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions.
