From the 1 of 8 linked papers with an AI index.
8 papers
Zero-Fi: Zero-Shot Wi-Fi-Based Human Activity Recognition via Contrastive Signal-Language Alignment
Yitong Shen, Cheng Guo, Peiliang Wang +5
Zero-Fi introduces a contrastive learning framework that aligns Wi‑Fi signal features with natural‑language descriptions of activities, enabling recognition of unseen human activit…
Understanding LLM Reasoning for Abstractive Summarization
Haohan Yuan, Haopeng Zhang
Reasoning has substantially improved Large Language Models (LLMs) on analytical tasks such as mathematics and code generation, but its value for abstractive summarization remains u…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
Position: Generative Engine Optimization Creates Underexamined Risks, Governance Must Target Concentration, Disclosure, and Academic Blind Spots
Yizhu Wen, Nan Zhang, Haohan Yuan +3
Large language model (LLM) answer engines are increasingly used for information seeking, shifting visibility from ranked lists to synthesized answers. This enables Generative Engin…
LLaTiSA: Towards Difficulty-Stratified Time Series Reasoning from Visual Perception to Semantics
Yueyang Ding, HaoPeng Zhang, Rui Dai +4
Comprehensive understanding of time series remains a significant challenge for Large Language Models (LLMs). Current research is hindered by fragmented task definitions and benchma…
StrucSum: Graph-Structured Reasoning for Long Document Extractive Summarization with LLMs
Haohan Yuan, Sukhwa Hong, Haopeng Zhang
Large language models (LLMs) have shown strong performance in zero-shot summarization, but often struggle to model document structure and identify salient information in long texts…