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cs.CL2026
G-Loss: Graph-Guided Fine-Tuning of Language Models
Aditya Sharma, Vinti Agarwal, Rajesh Kumar
Traditional loss functions, including cross-entropy, contrastive, triplet, and su pervised contrastive losses, used for fine-tuning pre-trained language models such as BERT, operat…
cs.CL2026
Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards
Luis Lara, Aristides Milios, Zhi Hao Luo +5
An AI system for professional floor plan design must precisely control room dimensions and areas while respecting the desired connectivity between rooms and maintaining functional…
cs.CL2024
Losing Visual Needles in Image Haystacks: Vision Language Models are Easily Distracted in Short and Long Contexts
Aditya Sharma, Michael Saxon, William Yang Wang
We present LoCoVQA, a dynamic benchmark generator for evaluating long-context extractive reasoning in vision language models (VLMs). LoCoVQA augments test examples for mathematical…