The predominance of English-language Web content creates an information-access barrier for speakers of low-resource languages such as Amharic. This paper presents the design, imple-mentation, and evaluation of a bidirectional Amharic-English cross-language question answering (CLQA) system that allows a user to formulat...
Large Vision-Language Models (LVLMs) have achieved remarkable progress across a wide range of multimodal tasks. However, object hallucination remains a persistent challenge, undermining model reliability in applications such as visual question answering, embodied agents, and human-AI decision support systems. In this p...
Xinhao Wang, Junbo Cui, Zhenghao Liu et al.· 0 citations
To enable large language models to generate outputs that align with human preferences, optimization algorithms based on the comparison between chosen and rejected output pairs have been developed and been proven effective. Some recent endeavors have utilized certain linguistically-derived assumptions about the preferen...
The first benchmark tailored for long historical document understanding is introduced, and various modal retrievers and the end-to-end RAG performance to provide references for Retrieval-Augmented Generation (RAG) systems are assessed.
Zeyu Shan, Yong-Xin Shi, Shi-Hang Wu et al.· 0 citations
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Deploying language models (LMs) on the edge presents unique memory, latency, and power challenges absent in high-performance computing. KV-cache compression emerges as a promising approach to address these challenges. However, the effectiveness of current KV-cache compression methods has not been thoroughly examined on...
S. M. Mahbub Murshed, Hayden Bright, Rezaul Karim et al.· 0 citations
In Chinese content governance, large language models are increasingly used to identify toxic and discriminatory expressions, yet both task operationalization and ironic expression can alter bias measurement readings. We conducted a preregistered multi-task behavioral audit of multiple Chinese large language models. In...
A challenging task in which an LLM predicts the relation between two glosses (definitions of senses) presented in two different orders, suggesting limitations in current LLMs's semantic relation knowledge, both in identifying relations and in respecting asymmetry.
Zhi-Han Cao, Adam Nohejl, Hitomi Yanaka· 0 citations
Large Language Models (LLMs) are increasingly being used to summarize and verify claims in critical sources that inform consequential decisions. Such claims are full of plural definites. If three of five patients improved after taking drug A, the claim the patients improved after drug A is not true, since two did not,...
Duaa Nakshbandi, Zhi-Yu An, Yi-Ping Li et al.· 0 citations
Scientific research increasingly depends on curating experimental data from literature. Scientific data curation requires verifying exact experimental conditions (e.g., specific assays, clinical outcomes, and data availability) across long, heterogeneous files, which is a highly time-consuming process. Existing benchma...
We show that continuous bitstream diffusion (CoBit), originally developed for language modeling, provides a unified framework for joint and conditional multimodal generation using the same training and sampling protocol. Across image-text, speech-text and protein sequence-structure modeling, models are trained separate...
Georgios Batzolis, Georgios Kontos, Bruno Trentini et al.· 0 citations
Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem through the lens of Skill LLMs: specialized executors that operate within a selected skill context and must complete a narrow, stateful workflow under policy and tool cons...
Md Tahmid Rahman Laskar, Gundeep Singh, Xue-Yong Fu et al.· 0 citations
Speech large language models (LLMs) are often built using pretrained acoustic encoders as an audio interface to an LLM decoder. However, LLMs scale poorly with input sequence length, while acoustic encoders tend to produce substantially longer sequences than typical textual inputs. This motivates learning to compress e...
Ci-Han Xiao, Yuan Tseng, Matthew Wiesner et al.· 0 citations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
