52 citations · 53 across the 8 of their papers we have counts for
9 papers
SynthDocBench: Controlled Benchmark for Long-Context Visual Document Understanding
Abhigya Verma, Khyati Mahajan, Amit Kumar Saha +4
Vision language models (VLMs) have achieved strong performance on visual document understanding benchmarks such as DocVQA, ChartQA, and MMLongBench-Doc. However, real-world documen…
Apriel-1.5-15b-Thinker
Shruthan Radhakrishna, Aman Tiwari, Aanjaneya Shukla +21
We present Apriel-1.5-15B-Thinker, a 15-billion parameter open-weights multimodal reasoning model that achieves frontier-level performance through training design rather than sheer…
AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs
Hoang Nguyen, Sidharth Surapaneni, Akshay Kalkunte +9
Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and non-standardized toolkits that limit fair comparison and s…
Apriel-Nemotron-15B-Thinker
Shruthan Radhakrishna, Soham Parikh, Gopal Sarda +32
While large language models (LLMs) have achieved remarkable reasoning capabilities across domains like code, math and other enterprise tasks, their significant memory and computati…
BigCharts-R1: Enhanced Chart Reasoning with Visual Reinforcement Finetuning
Ahmed Masry, Abhay Puri, Masoud Hashemi +13
Charts are essential to data analysis, transforming raw data into clear visual representations that support human decision-making. Although current vision-language models (VLMs) ha…
Augmenting LLM Reasoning with Dynamic Notes Writing for Complex QA
Rishabh Maheshwary, Masoud Hashemi, Khyati Mahajan +5
Iterative RAG for multi-hop question answering faces challenges with lengthy contexts and the buildup of irrelevant information. This hinders a model's capacity to process and reas…
Prompting with Phonemes: Enhancing LLMs' Multilinguality for Non-Latin Script Languages
Hoang H Nguyen, Khyati Mahajan, Vikas Yadav +4
Although multilingual LLMs have achieved remarkable performance across benchmarks, we find they continue to underperform on non-Latin script languages across contemporary LLM famil…
M2Lingual: Enhancing Multilingual, Multi-Turn Instruction Alignment in Large Language Models
Rishabh Maheshwary, Vikas Yadav, Hoang Nguyen +2
Instruction finetuning (IFT) is critical for aligning Large Language Models (LLMs) to follow instructions. While many effective IFT datasets have been introduced recently, they pre…
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…