activity
20232026
most citedEvaluating LLMs at Detecting Errors in LLM Responses

4 citations · 8 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

SIMMER: Benchmarking Latent Failures in LLM Executable Planning with a World Model

Xiaoxin Lu, Ranran Haoran Zhang, Rui Zhang

Large language models (LLMs) are increasingly deployed as planners for autonomous agents in household environments. While existing benchmarks evaluate whether LLM-generated plans e…

cs.AI2026

Bridging the Know-Act Gap via Task-Level Autoregressive Reasoning

Jihyun Janice Ahn, Ryo Kamoi, Berk Atil +34

LLMs often generate seemingly valid answers to flawed or ill-posed inputs. This is not due to missing knowledge: under discriminative prompting, the same models can mostly identify…

cs.CV2025

Enhance Multimodal Consistency and Coherence for Text-Image Plan Generation

Xiaoxin Lu, Ranran Haoran Zhang, Yusen Zhang +1

People get informed of a daily task plan through diverse media involving both texts and images. However, most prior research only focuses on LLM's capability of textual plan genera…

cs.CL2025

HRScene: How Far Are VLMs from Effective High-Resolution Image Understanding?

Yusen Zhang, Wenliang Zheng, Aashrith Madasu +14

High-resolution image (HRI) understanding aims to process images with a large number of pixels, such as pathological images and agricultural aerial images, both of which can exceed…

cs.CL2024★ 3 cited

AAAR-1.0: Assessing AI's Potential to Assist Research

Renze Lou, Hanzi Xu, Sijia Wang +15

Numerous studies have assessed the proficiency of AI systems, particularly large language models (LLMs), in facilitating everyday tasks such as email writing, question answering, a…

cs.CL2024★ 4 cited

Evaluating LLMs at Detecting Errors in LLM Responses

Ryo Kamoi, Sarkar Snigdha Sarathi Das, Renze Lou +12

With Large Language Models (LLMs) being widely used across various tasks, detecting errors in their responses is increasingly crucial. However, little research has been conducted o…

cs.CL2023★ 1 cited

Fair Abstractive Summarization of Diverse Perspectives

Yusen Zhang, Nan Zhang, Yixin Liu +9

People from different social and demographic groups express diverse perspectives and conflicting opinions on a broad set of topics such as product reviews, healthcare, law, and pol…