collaborators

9 papers

cs.CV2026

PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception

Yana Wei, Hongbo Peng, Yanlin Lai +14

We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness. Shifting evaluation from h…

cs.CV2026

3ViewSense: Spatial and Mental Perspective Reasoning from Orthographic Views in Vision-Language Models

Shaoxiong Zhan, Yanlin Lai, Zheng Liu +6

Current Large Language Models have achieved Olympiad-level logic, yet Vision-Language Models paradoxically falter on elementary spatial tasks like block counting. This capability m…

cs.CV2026

WebVR: Benchmarking Multimodal LLMs for WebPage Recreation from Videos via Human-Aligned Visual Rubrics

Yuhong Dai, Yanlin Lai, Mitt Huang +9

Existing web-generation benchmarks rely on text prompts or static screenshots as input. However, videos naturally convey richer signals such as interaction flow, transition timing,…

cs.CL2026

MathSmith: Towards Extremely Hard Mathematical Reasoning by Forging Synthetic Problems with a Reinforced Policy

Shaoxiong Zhan, Yanlin Lai, Ziyu Lu +3

Large language models have achieved substantial progress in mathematical reasoning, yet their advancement is limited by the scarcity of high-quality, high-difficulty training data.…

cs.CL2026

Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters

Ailin Huang, Ang Li, Aobo Kong +213

We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most wh…

cs.CL2026

PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and Engineering

Xiangfeng Wang, Hangyu Guo, Yanlin Lai +11

While model-based verifiers are essential for scaling Reinforcement Learning with Verifiable Rewards (RLVR), current outcome-centric verification paradigms primarily focus on the c…