3 papers
cs.AI2026
Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages
Chih-Hsuan Yang, Anjir Ahmed Chowdhury, Cheng-Hau Yang +7
Multi-agent reasoning systems often use agreement, confidence, or automated scores to decide which messages should shape a final answer. Such filtering assumes that a message likel…
cs.AI2026
Know When To Fold 'Em: Token-Efficient LLM Synthetic Data Generation via Multi-Stage In-Flight Rejection
Anjir Ahmed Chowdhury, Syed Zawad, Feng Yan
While synthetic data generation with large language models (LLMs) is widely used in post-training pipelines, existing approaches typically generate full outputs before applying qua…
cs.CL2026
PEML: Parameter-efficient Multi-Task Learning with Optimized Continuous Prompts
Anjir Ahmed Chowdhury, Syed Zawad, Xiaolong Ma +2
Parameter-Efficient Fine-Tuning (PEFT) is widely used for adapting Large Language Models (LLMs) for various tasks. Recently, there has been an increasing demand for fine-tuning a s…