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AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents

Lingxiang Hu, Yiding Sun, Tianle Xia, Wenwei Li, Ming Xu, Liqun Liu · Feb 15, 2026

Citations: 0
Expert Verification Simulation Env Long Horizon Coding
  • While Large Language Model (LLM) agents have achieved remarkable progress in complex reasoning tasks, evaluating their performance in real-world environments has become a critical problem.
  • To address this gap, we propose AD-Bench, a benchmark designed based on real-world business requirements of advertising and marketing platforms.
Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception

Lai Wei, Liangbo He, Jun Lan, Lingzhong Dong, Yutong Cai, Siyuan Li · Feb 12, 2026

Citations: 0
Automatic Metrics Tool Use Coding
  • To address this, we propose Region-to-Image Distillation, which transforms zooming from an inference-time tool into a training-time primitive, thereby internalizing the benefits of agentic zooming into a single forward pass of an MLLM.
  • To rigorously evaluate this capability, we further present ZoomBench, a hybrid-annotated benchmark of 845 VQA data spanning six fine-grained perceptual dimensions, together with a dual-view protocol that quantifies the global--regional…
Structurally Aligned Subtask-Level Memory for Software Engineering Agents

Kangning Shen, Jingyuan Zhang, Chenxi Sun, Wencong Zeng, Yang Yue · Feb 25, 2026

Citations: 0
Automatic Metrics Long Horizon Coding
  • Large Language Models (LLMs) have demonstrated significant potential as autonomous software engineering (SWE) agents.
  • Recent work has further explored augmenting these agents with memory mechanisms to support long-horizon reasoning.
REDSearcher: A Scalable and Cost-Efficient Framework for Long-Horizon Search Agents

Zheng Chu, Xiao Wang, Jack Hong, Huiming Fan, Yuqi Huang, Yue Yang · Feb 15, 2026

Citations: 0
Automatic Metrics Tool Use Coding
  • To address these challenges, we propose REDSearcher, a unified framework that codesigns complex task synthesis, midtraining, and posttraining for scalable searchagent optimization.
  • Across both textonly and multimodal searchagent benchmarks, our approach achieves stateoftheart performance.

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