13 papers · 1 filter
A Toolbox, Not a Hammer -- Multi-TAG: Scaling Math Reasoning with Multi-Tool Aggregation
Bohan Yao, Vikas Yadav
Augmenting large language models (LLMs) with external tools is a promising avenue for developing high-performance mathematical reasoning systems. Prior tool-augmented approaches ty…
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…
Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models
Meghana Rajeev, Rajkumar Ramamurthy, Prapti Trivedi +5
We investigate the robustness of reasoning models trained for step-by-step problem solving by introducing query-agnostic adversarial triggers - short, irrelevant text that, when ap…
CopySpec: Accelerating LLMs with Speculative Copy-and-Paste Without Compromising Quality
Razvan-Gabriel Dumitru, Minglai Yang, Vikas Yadav +1
We introduce CopySpec, a simple yet effective technique to tackle the inefficiencies LLMs face when generating responses that closely resemble previous outputs or responses that ca…
ConciseRL: Conciseness-Guided Reinforcement Learning for Efficient Reasoning Models
Razvan-Gabriel Dumitru, Darius Peteleaza, Vikas Yadav +1
Large language models excel at complex tasks by breaking down problems into structured reasoning steps. However, reasoning traces often extend beyond reaching a correct answer, cau…
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…