discover
Datasets
All datasets matching “discover”dim-discovery-archive
Geometry of Decision Making in Language Models
Abhinav Joshi · Divyanshu Bhatt · Ashutosh ModiNeurIPS 2025
This repository contains the official implementation/release for the NeurIPS 2025 paper Geometry of Decision Making in Language Models.
We study the internal decision-making processes of large language models through the lens of intrinsic dimension (ID), analyzing how hidden representations evolve across layers in a multiple-choice… See the full description on the dataset page: https://huggingface.co/datasets/Exploration-Lab/dim-discovery-archive.discover-toolsequity-perp-price-discovery
Equity and pre-IPO perpetual prices
Snapshots of perpetual-futures mark prices, index prices and basis from Aevo. The instrument universe includes equities, ETFs, commodities, foreign exchange, pre-IPO contracts and crypto assets.
Contents
Table
Record
perpetual_mark_and_index_prices
An instrument's mark price, index price and basis at an observation time
Using the data
market_type identifies the instrument category. is_rwa flags the… See the full description on the dataset page: https://huggingface.co/datasets/dataforge-labs/equity-perp-price-discovery.discoverybenchData-driven Discovery Benchmark from the paper:
"DiscoveryBench: Towards Data-Driven Discovery with Large Language Models"
🔭 Overview
DiscoveryBench is designed to systematically assess current model capabilities in data-driven discovery tasks and provide a useful resource for improving them. Each DiscoveryBench task consists of a goal and dataset(s). Solving the task requires both statistical analysis and semantic reasoning. A faceted evaluation allows open-ended… See the full description on the dataset page: https://huggingface.co/datasets/allenai/discoverybench.discoverphysics-kimi-k2.7-ara
DiscoverPhysics × Kimi K2.7 (kimi-code CLI, thinking=on) — 11-world ARA knowledge artifacts
Agent-Native Research Artifacts (ARA) produced by a Kimi K2.7 (kimi-code CLI, thinking=on) coding-agent session solving all
11 worlds of the DiscoverPhysics scientific-discovery
benchmark (seed 0, noise_frac 0.075, ≤16 experiment rounds), driven through the same
harness-agnostic bridge and ARA scaffold as the sibling fable run. Official verdicts:
1/11 PASS — criteria and per-world numbers… See the full description on the dataset page: https://huggingface.co/datasets/AgentNativeResearchLab/discoverphysics-kimi-k2.7-ara.Discoverse-L
This dataset is the result of joint research conducted by Hao Tang's team at the School of Computer Science, Peking University, and the Beijing Academy of Artificial Intelligence (BAAI).
Paper: EvoVLA: Self-Evolving Vision-Language-Action Model
Authors: Zeting Liu*, Zida Yang*, Zeyu Zhang*†, Hao Tang‡Institution: Peking University
Overview
Discoverse-L is a long-horizon manipulation benchmark built on the DISCOVERSE simulator with AIRBOT-Play robot platform. It… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/Discoverse-L.
