Measures when LLMs produce visible reasoning despite instructions not to, introducing three response-level metrics (Empty-Thinking Rate, Question–Pre-answer Relevance, Explicit Inference Rate) and evaluating 'no-thinking' behavior across tasks, models, and prompting interventions.
AI Video Papers2026
Converts static 3D Gaussian Splatting scenes into endlessly looping 3D cinemagraphs by inferring plausible dynamics with a vision-language model, synthesizing a reference video, lifting it to multi-view videos, and fitting a Fourier-parameterized Periodic Deformation Field with a Grounded Drift Field—mask-free capture of deformation, object motion, and illumination changes.
AI Agent Papers2026
Jiahao Wang, Hongjin Qian +3Beijing Academy of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences +1
Measures whether coding agents can build agents that truly satisfy natural-language requirements via AgentSWE: a 25-task benchmark spanning Creation, Editing, and Optimization. Builders develop against few illustrative cases; acceptance runs frozen submissions on held-out cases and requirement-derived rubrics, exposing overfitting, hollow runtimes, and unsupported completion claims.
AI Model2026
A System 1 multimodal decision model that picks among up to 256 options and returns calibrated probabilities for choice, yes/no and 0–5 score decisions from text and images. Fine-tuned on Qwen3.5-35B-A3B, available in bf16 and NVFP4 builds (NVFP4 fits ~23.3 GiB GPU), and served via vLLM's POST /v1/decide API.