163 citations · 539 across the 205 of their papers we have counts for
41 papers · 1 filter
Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability
Haonan Li, Xudong Han, Zenan Zhai +32
To address this gap, we introduce Libra-Leaderboard, a comprehensive framework designed to rank LLMs through a balanced evaluation of performance and safety. Combining a dynamic le…
MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media
Muhammad Arslan Manzoor, Ruihong Zeng, Dilshod Azizov +2
In the current era of rapidly growing digital data, evaluating the political bias and factuality of news outlets has become more important for seeking reliable information online.…
Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models
Lang Gao, Jiahui Geng, Xiangliang Zhang +2
Jailbreaking in Large Language Models (LLMs) is a major security concern as it can deceive LLMs to generate harmful text. Yet, there is still insufficient understanding of how jail…
Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve Framework
Jundong Xu, Hao Fei, Meng Luo +6
In the context of large language models (LLMs), current advanced reasoning methods have made impressive strides in various reasoning tasks. However, when it comes to logical reason…
Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks
Jinyan Su, Jin Peng Zhou, Zhengxin Zhang +2
Retrieval-Augmented Generation (RAG) systems have emerged as a promising solution to mitigate LLM hallucinations and enhance their performance in knowledge-intensive domains. Howev…
Learning To Sample the Meta-Paths for Social Event Detection
Congbo Ma, Hu Wang, Zitai Qiu +5
Social media data is inherently rich, as it includes not only text content, but also users, geolocation, entities, temporal information, and their relationships. This data richness…
MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation
Harsh Singh, Rocktim Jyoti Das, Mingfei Han +2
Large Language Models (LLMs) have demonstrated remarkable planning abilities across various domains, including robotics manipulation and navigation. While recent efforts in robotic…
FIRE: Fact-checking with Iterative Retrieval and Verification
Zhuohan Xie, Rui Xing, Yuxia Wang +5
Fact-checking long-form text is challenging, and it is therefore common practice to break it down into multiple atomic claims. The typical approach to fact-checking these atomic cl…
DocEdit-v2: Document Structure Editing Via Multimodal LLM Grounding
Manan Suri, Puneet Mathur, Franck Dernoncourt +5
Document structure editing involves manipulating localized textual, visual, and layout components in document images based on the user's requests. Past works have shown that multim…
Loki: An Open-Source Tool for Fact Verification
Haonan Li, Xudong Han, Hao Wang +7
We introduce Loki, an open-source tool designed to address the growing problem of misinformation. Loki adopts a human-centered approach, striking a balance between the quality of f…
Arabic Dataset for LLM Safeguard Evaluation
Yasser Ashraf, Yuxia Wang, Bin Gu +2
The growing use of large language models (LLMs) has raised concerns regarding their safety. While many studies have focused on English, the safety of LLMs in Arabic, with its lingu…
PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
Jiateng Liu, Lin Ai, Zizhou Liu +6
Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the…
Exploring Language Model Generalization in Low-Resource Extractive QA
Saptarshi Sengupta, Wenpeng Yin, Preslav Nakov +2
In this paper, we investigate Extractive Question Answering (EQA) with Large Language Models (LLMs) under domain drift, i.e., can LLMs generalize to domains that require specific k…
Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect
Guokan Shang, Hadi Abdine, Yousef Khoubrane +9
We introduce Atlas-Chat, the first-ever collection of LLMs specifically developed for dialectal Arabic. Focusing on Moroccan Arabic, also known as Darija, we construct our instruct…
TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning
Xinyuan Lu, Liangming Pan, Yubo Ma +2
Current Large Language Models (LLMs) exhibit limited ability to understand table structures and to apply precise numerical reasoning, which is crucial for tasks such as table quest…
Post-OCR Text Correction for Bulgarian Historical Documents
Angel Beshirov, Milena Dobreva, Dimitar Dimitrov +3
The digitization of historical documents is crucial for preserving the cultural heritage of the society. An important step in this process is converting scanned images to text usin…
Grounding Fallacies Misrepresenting Scientific Publications in Evidence
Max Glockner, Yufang Hou, Preslav Nakov +1
Health-related misinformation claims often falsely cite a credible biomedical publication as evidence. These publications only superficially seem to support the false claim, when l…
OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs
Hasan Iqbal, Yuxia Wang, Minghan Wang +4
The increased use of large language models (LLMs) across a variety of real-world applications calls for automatic tools to check the factual accuracy of their outputs, as LLMs ofte…
Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing +7
Uncertainty quantification (UQ) has emerged as a promising approach for detecting hallucinations and low-quality output of Large Language Models (LLMs). However, obtaining proper u…
LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection
Mervat Abassy, Kareem Elozeiri, Alexander Aziz +21
The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written o…
Bilingual Adaptation of Monolingual Foundation Models
Gurpreet Gosal, Yishi Xu, Gokul Ramakrishnan +19
We present an efficient method for adapting a monolingual Large Language Model (LLM) to another language, addressing challenges of catastrophic forgetting and tokenizer limitations…
Missci: Reconstructing Fallacies in Misrepresented Science
Max Glockner, Yufang Hou, Preslav Nakov +1
Health-related misinformation on social networks can lead to poor decision-making and real-world dangers. Such misinformation often misrepresents scientific publications and cites…
Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs
Sukmin Yun, Haokun Lin, Rusiru Thushara +14
Multimodal large language models (MLLMs) have shown impressive success across modalities such as image, video, and audio in a variety of understanding and generation tasks. However…
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev +12
The rapid proliferation of large language models (LLMs) has stimulated researchers to seek effective and efficient approaches to deal with LLM hallucinations and low-quality output…