12 citations · 13 across the 10 of their papers we have counts for
7 papers · 1 filter
Second-Order Problem Solving for Recursive Self-Improvement in Formal Verification
Yuxuan Jiang, Aditya Vempaty, Ashish Jagmohan
Recursive self-improvement (RSI) enables agents to iteratively optimize their workflows via execution feedback. However, standard RSI typically operates as a first-order optimizer:…
New Evidence, Same Choice: Testing Physical Experiment Selection in Vision Language Models
Sourajit Saha, Shubhashis Roy Dipta, Nobin Sarwar +4
A model first sees an image from one physical measurement experiment, such as how far a block coasted, and must answer a question about a new trial, such as whether the block will…
BEFORE THE FLIP: Measuring Hidden Score Shifts In Quantized Vision Language Models Before The Answer Changes for Visual Question Answering
Sourajit Saha, Shubhashis Roy Dipta, Shaswati Saha +2
Quantization makes vision language models (VLMs) cheaper to store and run by using fewer bits to represent their weights. While unchanged answers on visual question answering (VQA)…
Cornerstones or Stumbling Blocks? Deciphering the Rock Tokens in On-Policy Distillation
Yuxuan Jiang, Runchao Li, Shubhashis Roy Dipta +2
While recent work in Reinforcement Learning with Verifiable Rewards (RLVR) has shown that a small subset of critical tokens disproportionately drives reasoning gains, an analogous…
Bridging Reasoning Trajectories in On-Policy Distillation via Near-Future Guidance
Yuxuan Jiang, Francis Ferraro
On-Policy Distillation (OPD) improves large language model reasoning by training a student model on trajectories sampled from its own policy under teacher supervision. Although OPD…
From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding
Yandi Wang, Libin Zhan, Ziwei Huang +5
Extracting structured information from visual documents (Visual Information Extraction, VIE) is a cornerstone of business automation. While recent Multimodal Large Language Models…
SCRIBE: Structured Mid-Level Supervision for Tool-Using Language Models
Yuxuan Jiang, Francis Ferraro
Training reliable tool-augmented agents remains a significant challenge, largely due to the difficulty of credit assignment in multi-step reasoning. While process-level reward mode…