Daniil Orel

Jais 2: A Family of Arabic-Centric Open Large Language Models

Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, Mostafa Awad et autres

Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong performance across the Arabic and culturally grounded benchmarks evaluated in this report. The family includes, to our …

Parameter estimation horizon of core-collapse supernovae with current and next-generation gravitational-wave detectors

Almat Akhmetali, Y. S. Abylkairov, Daniil Orel, Solange da Silva Nunes et autres

Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova central engine. In this work, we investigate parameter estimation from the bounce and early ring-down GW signal of rotating CCSNe …

kz, ae, pt, es (code pays fourni par la source)

Parameter Estimation Horizon of Core-Collapse Supernovae with Current and Next-Generation Gravitational-Wave Detectors

Almat Akhmetali, Y. Sultan Abylkairov, Daniil Orel, Solange Nunes et autres

Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova central engine. In this work, we investigate parameter estimation from the bounce and early ring-down GW signal of rotating CCSNe …

A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis

Muhammad Arslan Manzoor, Dilshod Azizov, Daniil Orel, Umer Siddique et autres

News outlets shape public opinion at a scale that makes automated detection of political bias and factuality essential. However, the field still lacks unified resources, comprehensive evaluations across diverse approaches, and systematic analyses of the representations and fusion strategies that matter most, …

A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis

Muhammad Arslan Manzoor, Dilshod Azizov, Daniil Orel, Umer Siddique et autres

News outlets shape public opinion at a scale that makes automated detection of political bias and factuality essential. However, the field still lacks unified resources, comprehensive evaluations across diverse approaches, and systematic analyses of the representations and fusion strategies that matter most, …

us, dk (code pays fourni par la source)

Why Don't You Know? Evaluating the Impact of Uncertainty Sources on Uncertainty Quantification in LLMs

Maiya Goloburda, Roman Vashurin, Fedor Chernogorsky, Nurkhan Laiyk et autres

As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe and effective use. Most existing UQ approaches for language models aim to produce a single confidence score -- for example, estimating the probability …

Why Don't You Know? Evaluating the Impact of Uncertainty Sources on Uncertainty Quantification in LLMs

Maiya Goloburda, Roman Vashurin, Fedor Chernogorsky, Nurkhan Laiyk et autres

As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe and effective use. Most existing UQ approaches for language models aim to produce a single confidence score -- for example, estimating the probability …

ca (code pays fourni par la source)

AICD Bench: A Challenging Benchmark for AI-Generated Code Detection

Daniil Orel, Dilshod Azizov, Indraneil Paul, Yuxia Wang et autres

Large language models (LLMs) are increasingly capable of generating functional source code, raising concerns about authorship, accountability, and security. While detecting AI-generated code is critical, existing datasets and benchmarks are narrow, typically limited to binary human-machine classification under in-distribution settings. To bridge …

AICD Bench: A Challenging Benchmark for AI-Generated Code Detection

Daniil Orel, Dilshod Azizov, Indraneil Paul, Yuxia Wang et autres

Large language models (LLMs) are increasingly capable of generating functional source code, raising concerns about authorship, accountability, and security. While detecting AI-generated code is critical, existing datasets and benchmarks are narrow, typically limited to binary human-machine classification under in-distribution settings. To bridge …

ae, us, bg (code pays fourni par la source)

A benchmark of expert-level academic questions to assess AI capabilities

Alice Gatti, Nathaniel Li, Adam Khoja, Ryan Kim et autres

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve more than 90% accuracy on popular benchmarks such as Measuring Massive Multitask Language Understanding1, limiting informed …

us, id, gb, in, fr, ca, ua, bs, de (code pays fourni par la source)

A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens, Wei He et autres

Potentially idiomatic expressions (PIEs) construe meanings inherently tied to the everyday experience of a given language community. As such, they constitute an interesting challenge for assessing the linguistic (and to some extent cultural) capabilities of NLP systems. In this paper, we present …

A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding

Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens, Wei He et autres

Potentially idiomatic expressions (PIEs) construe meanings inherently tied to the everyday experience of a given language community. As such, they constitute an interesting challenge for assessing the linguistic (and to some extent cultural) capabilities of NLP systems. In this paper, we present …