activity
20212026
most citedFew-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning

294 citations · 307 across the 17 of their papers we have counts for

collaborators

17 papers

cs.AI2026

GTA: Generating Long-Horizon Tasks for Web Agents at Scale

Tenghao Huang, Kung-Hsiang Huang, Prafulla Kumar Choubey +4

Web agents, which couple language models with browsing and tool-use capabilities, show promise as open web assistants. Yet progress is increasingly limited by the lack of scalable,…

cs.CR2026

Cooking Up Risks: Benchmarking and Reducing Food Safety Risks in Large Language Models

Weidi Luo, Xiaofei Wen, Tenghao Huang +5

Large language models (LLMs) are increasingly deployed for everyday tasks, including food preparation and health-related guidance. However, food safety remains a high-stakes domain…

cs.CL2025

Optimizing Diversity and Quality through Base-Aligned Model Collaboration

Yichen Wang, Chenghao Yang, Tenghao Huang +3

Alignment has greatly improved large language models (LLMs)' output quality at the cost of diversity, yielding highly similar outputs across generations, especially in open-ended g…

cs.AI2025

Teaching Language Models To Gather Information Proactively

Tenghao Huang, Sihao Chen, Muhao Chen +4

Large language models (LLMs) are increasingly expected to function as collaborative partners, engaging in back-and-forth dialogue to solve complex, ambiguous problems. However, cur…

cs.CL2025

DiscoSum: Discourse-aware News Summarization

Alexander Spangher, Tenghao Huang, Jialiang Gu +2

Recent advances in text summarization have predominantly leveraged large language models to generate concise summaries. However, language models often do not maintain long-term dis…

cs.AI2025

R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory

Tenghao Huang, Kinjal Basu, Ibrahim Abdelaziz +3

The proliferation of web agents necessitates advanced navigation and interaction strategies within complex web environments. Current models often struggle with efficient navigation…