AI Agent Papers2026
Extracts replayable behaviors from working web apps and converts them into verifiable, reference-guided software-engineering tasks to evaluate and diagnose coding agents; includes an automated pipeline that scales to thousands of tasks.
Enables specifying exact 24-bit hex colors for object-level image generation and editing via a unified prompt interface, using a Paint-500K dataset and timestep-gated pure-color anchors to improve color fidelity.
AI Dataset2026
Provides a complete benchmark and training release for native audio‑visual dialogue: 2,800 synthesized audio‑visual dialogues, tiered rubrics, scoring code, ~28GB of 1080p media, and an RL reward recipe to evaluate and train omni models that take video+audio and return text.
AI Video Papers2026
Zhenchen Tang, Yang Li +7New Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, School of Artificial Intelligence, University of Chinese Academy of Sciences +2
Introduces a rubric-based approach for video reward modeling that generates explicit, query-adaptive evaluation criteria before scoring to reduce scalar drift; proposes RGPO, a two-stage training (seed warm-up + joint optimization) that achieves strong pointwise and pairwise evaluation with high data efficiency.
Embodied AI2026
Uses a compact discrete-action interface (translation, rotation, gripper) to let frozen vision–language models control robots in closed-loop, and leverages in-context (one-shot) demonstrations to substantially improve manipulation success without robot-specific training.
Provides an open family of K–12 foundation models and a capability-oriented instruction-tuning corpus that teaches models to solve curriculum problems, map items to curriculum concepts, diagnose learner errors, and produce scaffolded pedagogical responses.
AI Agent Papers2026
Ruixun Liu, Yuxuan Wang +11School of Intelligence Science and Technology, Peking University, State Key Laboratory of General Artificial Intelligence, Peking University +2
Provides a unified benchmark and a spatially aware omni-modal model for spatial audio-visual reasoning in embodied agents — OmniEchoBench (197 scenes, 2,972 QA pairs; 900 FOA-based navigation tasks) plus OmniEcho, which adds an FOA spatial encoder to a pretrained semantic audio pathway to enable spatial QA and sound-guided navigation.
AI Image2026
Provides multiple quantized releases (GGUF, safetensors, MLX) of Qwen-Image-2.1 for local text-to-image generation; includes GPU- and Apple-Silicon–optimized quantizations, companion text encoders/VAEs, and recommended ComfyUI configurations.
Hangyu Ran, Yuhao Zheng +3Ant Group, The Hong Kong University of Science and Technology (Guangzhou) +2
Converts natural-language SVG instructions into instance-aware six-item rubrics and uses a vision–language judge to score rendered SVGs item-by-item as dense RL rewards. Produces stronger human alignment and lifts benchmark rubric scores substantially on MMSVG datasets.
An all-in-one multilingual scene text recognition approach that pairs a shared visual encoder with a script-aware Mixture-of-Experts (ScriptMoE) decoder to route each image to top-2 script experts. Introduces TextMuSS-10M, a synthetic dataset covering 10 scripts and 229 languages, and reports state-of-the-art accuracy and large end-to-end OCR F1 gains while remaining parameter-efficient.
AI Model2026
Scores candidate actions against a textual state using contrastive state/action embeddings for very fast zero-shot ranking and typed decision-making. Built as two small projection heads on frozen Qwen3-8B; fine-tunable as a verifier for agentic benchmarks.
Yiran Wang, Xingyilang Yin +13Affiliation: ARC Lab, Tencent, Affiliation: GVC Lab, Great Bay University +4
Provides a unified data and evaluation suite for measuring gameplay capabilities across short, medium, and long temporal horizons. Includes an automated annotator, a 5,000-hour AAA gameplay dataset with temporally aligned frames, actions and multi-horizon instructions, and a reproducible offline + stepwise online benchmark.