9 papers
Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models
Jiawei Xu, Minghui Liu, Aakriti Agrawal +2
Masked diffusion language models decode by iteratively unmasking tokens, where the unmasking order defines an "order of thought" that strongly influences generation quality yet is…
Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings
Aakriti Agrawal, Gouthaman KV, Rohith Aralikatti +6
Hallucinations in Large Vision-Language Models (LVLMs) remain a persistent challenge, often stemming from inadequate integration of visual information during multimodal reasoning.…
The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning
Aakriti Agrawal, Souradip Chakraborty, Armin Saghafian +6
Process Reward Models (PRMs) improve credit assignment for reasoning by providing step-level feedback. However, we identify a hidden bias in PRMs caused by severe imbalance in step…
VeriGate: Verifier-Gated Step-Level Supervision for GRPO
Aakriti Agrawal, Minghui Liu, Furong Huang
Group Relative Policy Optimization (GRPO) is an effective recipe for training reasoning models with verifier-based outcome rewards, but its supervision is sparse: when all sampled…
Uncertainty-Aware Answer Selection for Improved Reasoning in Multi-LLM Systems
Aakriti Agrawal, Rohith Aralikatti, Anirudh Satheesh +3
Large Language Models (LLMs) have demonstrated exceptional capabilities, yet selecting the most reliable response from multiple LLMs remains a challenge, particularly in resource-c…
EnsemW2S: Enhancing Weak-to-Strong Generalization with Large Language Model Ensembles
Aakriti Agrawal, Mucong Ding, Zora Che +6
With Large Language Models (LLMs) rapidly approaching and potentially surpassing human-level performance, it has become imperative to develop approaches capable of effectively supe…