#Research
Curated coverage on «Research»: releases, research, benchmarks, open-source.
DISC Learns to Combine Time-Series Similarity Metrics and Predict Transfer Success
DISC, a new learnable framework, calibrates and combines dataset similarity metrics for time series to estimate in advance how well a forecast will transfer from a…
MMVistaReason: Open Recipe Trains a 4B Model That Beats Qwen3.5-9B on 15 Benchmarks
The MMVistaReason authors released an open post-training recipe: MVR-4B scored 72.8 across 15 multimodal benchmarks, beating Qwen3.5-9B (Instruct).
Survey by Shengqiong Wu and Hao Fei: 600+ Papers on Video Models as World Models
A team including Shuicheng Yan, Ming-Hsuan Yang and Philip Torr unifies video understanding and generation in one framework and reviews more than 600 papers across…
Lafa, an 8B-parameter model, speeds up text generation by 2.54x without sacrificing quality
EvaOmni Benchmark Tests 24 Omni Models: Leader Scores 79.4% Accuracy, but Only 35.1% on Grounding
Video-Point Model Predicts Multi-Camera Video and 3D Point Trajectories
Recursive Self-Improvement and Fable 5.1: Why the AI Race Moved Past AGI Debates Into Applied Orchestration
Layer Looping Cuts Diffusion LLM Training Costs by Up to 3.3x
Looping early transformer layers at every denoising step cut training costs for uniform diffusion language models by up to 2.8x on OpenWebText and 3.3x on…
SplatLab writes its own 3D Gaussian Splatting papers and beats baselines by up to +3.78 dB
An autonomous system reproduces a 3DGS paper, proposes an extension, trains models, and writes a manuscript. PSNR gains over baselines range from +0.18 to +3.78 dB.
ToM2Vec Teaches LLM Agents to Model Their Partners in Latent Tokens
LASAGNA Tests 450 RAG Configurations: The Promised +47% Gain Turns Into Just +17%
LoopRec Picks Compute Depth for Each Item and Beats Baselines on 4 Backbones
RealMe Builds 2K Volumetric Video from a Handful of Cameras Using Diffusion
Researchers Propose PAPAV Framework: Only 3 of 64 Benchmarks Test Verification
A new paper compares computer-use agents and robots through five PAPAV functions. Of 64 benchmarks, 5 assess outcome prediction and only 3 assess result…
NUS Teaches a Model to Find What It Described: gIoU Rises From 57.5% to 68.2%
Generalized CycleGRPO links describing a region and finding it from text in a single RL loop, with no reference captions and no LLM judge. On GroundingSuite, gIoU…