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All datasets matching “sigs”VeriLoop-Coder-E1-Evaluation-Evidence
VeriLoop Coder-E1 Evaluation Evidence
This repository contains the public evaluation-evidence packages
referenced by the official VeriLoop Coder-E1 benchmark result files.
Model repository:
tsinghua-sigs-robot-lab/veriloop-coder-e1
Evidence packages
Benchmark
Evidence directory
DeepSWE
veriloop-coder-e1-deepswe-evaluation-evidence-v1.0.0
SWE-bench Pro
veriloop-coder-e1-swe-bench-pro-evaluation-evidence-v1.0.0
SWE-bench Verified… See the full description on the dataset page: https://huggingface.co/datasets/tsinghua-sigs-robot-lab/VeriLoop-Coder-E1-Evaluation-Evidence.VeriLoop-E2-Evaluation-Evidence
VeriLoop E2 Evaluation Evidence
Public evaluation evidence for VeriLoop E2 across nine code, agentic, mathematical, and scientific reasoning benchmarks.
This dataset repository is the canonical public evidence layer for the reported benchmark results of VeriLoop E2, a post-trained model based on Qwen 3.8-27B. It is designed to separate headline benchmark reporting from the underlying auditable artifacts required to inspect, reproduce, and verify those results.
The repository… See the full description on the dataset page: https://huggingface.co/datasets/tsinghua-sigs-robot-lab/VeriLoop-E2-Evaluation-Evidence.qwen3.8-conv1d-sigscalesync
The conv1d sigma outliers in Qwen3.8-27B are real. The quantization story attached to them is not — and the rescale variant I tested cost perplexity while fixing nothing measurable.
Scope revision (2026-08-24). An earlier version of this README said the rescale was applied
"exactly as published" and that the mechanism "cannot work". Both were too strong. What I tested
is a 7-tensor median-normalization variant (σ > 1.5× median → α = median/σ); the intervention
actually… See the full description on the dataset page: https://huggingface.co/datasets/windowsxp811203/qwen3.8-conv1d-sigscalesync.MapReader_Data_SIGSPATIAL_2022TODOAgenticVLA_peach_into_drawerThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "piper_follower",
"total_episodes": 100,
"total_frames": 30219,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 500,
"fps": 30,
"splits": {
"train": "0:100"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/sigs-eilab/AgenticVLA_peach_into_drawer.bimanual_stack_cup_bowlThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"left_joint_1.pos",
"left_joint_2.pos",
"left_joint_3.pos",
"left_joint_4.pos",
"left_joint_5.pos",
"left_joint_6.pos",
"left_gripper.pos"… See the full description on the dataset page: https://huggingface.co/datasets/THU-SIGS-EILAB/bimanual_stack_cup_bowl.