most citedMaking Large Language Models Better Reasoners with Alignment

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

PCA-Bench: Evaluating Multimodal Large Language Models in Perception-Cognition-Action Chain

Liang Chen, Yichi Zhang, Shuhuai Ren +7

We present PCA-Bench, a multimodal decision-making benchmark for evaluating the integrated capabilities of Multimodal Large Language Models (MLLMs). Departing from previous benchma…

cs.IT2023

Semantic-Relay-Aided Text Transmission: Placement Optimization and Bandwidth Allocation

Tianyu Liu, Changsheng You, Zeyang Hu +3

Semantic communication has emerged as a promising technology to break the Shannon limit by extracting the meaning of source data and sending relevant semantic information only. How…

eess.SP2023

Multiuser Resource Allocation for Semantic-Relay-Aided Text Transmissions

Zeyang Hu, Tianyu Liu, Changsheng You +2

Semantic communication (SemCom) is an emerging technology that extracts useful meaning from data and sends only relevant semantic information. Thus, it has the great potential to i…

cs.CL20235 cited

Making Large Language Models Better Reasoners with Alignment

Peiyi Wang, Lei Li, Liang Chen +5

Reasoning is a cognitive process of using evidence to reach a sound conclusion. The reasoning capability is essential for large language models (LLMs) to serve as the brain of the…

cs.CL20233 cited

Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus

Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma +3

Several recent papers claim human parity at sentence-level Machine Translation (MT), especially in high-resource languages. Thus, in response, the MT community has, in part, shifte…