5 papers
Teaching AI Through Benchmark Construction: QuestBench as a Course-Based Practice for Accountable Knowledge Work
Haiyang Shen, Jiuzheng Wang, Taian Guo +9
As AI becomes part of everyday learning, many courses teach students to use it mainly as a productivity tool: how to prompt, search, summarize, write, code, and use tools more effi…
MindLoom: Composing Thought Modes for Frontier-Level Reasoning Data Synthesis
Haiyang Shen, Taian Guo, Xuanzhong Chen +11
Although LLMs have made substantial progress in reasoning, systematically producing frontier-level reasoning data remains difficult. Existing synthesis methods often have limited v…
DeepWeb-Bench: A Deep Research Benchmark Demanding Massive Cross-Source Evidence and Long-Horizon Derivation
Sixiong Xie, Zhuofan Shi, Haiyang Shen +8
Deep research, in which an agent searches the open web, collects evidence, and derives an answer through extended reasoning, is a prominent use case for frontier language models. F…
A First Look at Bugs in LLM Inference Engines
Mugeng Liu, Siqi Zhong, Weichen Bi +5
Large language model-specific inference engines (in short as \emph{LLM inference engines}) have become a fundamental component of modern AI infrastructure, enabling the deployment…
WebANNS: Fast and Efficient Approximate Nearest Neighbor Search in Web Browsers
Mugeng Liu, Siqi Zhong, Qi Yang +3
Approximate nearest neighbor search (ANNS) has become vital to modern AI infrastructure, particularly in retrieval-augmented generation (RAG) applications. Numerous in-browser ANNS…