most citedMM-PhyRLHF: Reinforcement Learning Framework for Multimodal Physics Question-Answering

4 citations · 4 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2026

DirectSpeech2LLM: A Simple End-to-End Framework to Mitigate Prompt Overfitting in Speech-LLMs

Hemant Yadav, Sunayana Sitaram, Roger Zimmermann +1

Speech-LLMs often exhibit prompt overfitting, where models solely trained on automatic speech recognition (ASR) instruction fail to generalize to new instructions such as speech tr…

cs.AI2026

Trading Strategy Optimization via Textual Gradient

Chaoqun Yang, Qian Wang, Fengbin Zhu +4

Quantitative trading strategy design aims to discover trading programs from historical data that remain effective in future markets, which can be viewed as a black-box program opti…

cs.AI2026

Evaluating Rational Contracting in Natural Language

Bhavyesh Sajja, Max Kleiman-Weiner, Roger Zimmermann +1

The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard-coded protocols, such agent…

cs.CV2026

JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles

Shawn Li, Wei Yang, Jike Zhong +11

Jigsaw puzzle solving requires jointly reasoning about visual content and geometric constraints, yet existing benchmarks use rectangular cuts that create ambiguous ground truth in…

cs.AI2026

FinDeepIndicator: Benchmarking Deep Research Agents in End-to-End Financial Indicator Construction

Chaoqun Yang, Fengbin Zhu, Xinyu Lin +5

Financial indicators are essential tools for transforming raw financial data into interpretable measures for various downstream tasks, such as valuation, risk assessment, and econo…

cs.CV2026

Make Your LVLM KV Cache More Lightweight

Xihao Chen, Yangyang Guo, Roger Zimmermann

Key-Value (KV) cache has become a de facto component of modern Large Vision-Language Models (LVLMs) for inference. While it enhances decoding efficiency in Large Language Models (L…

cs.AI2024

Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring

Avinash Anand, Raj Jaiswal, Abhishek Dharmadhikari +6

This paper presents GPSM4K, a comprehensive geometry multimodal dataset tailored to augment the problem-solving capabilities of Large Vision Language Models (LVLMs). GPSM4K encompa…

cs.IR2024

CIRP: Cross-Item Relational Pre-training for Multimodal Product Bundling

Yunshan Ma, Yingzhi He, Wenjun Zhong +3

Product bundling has been a prevailing marketing strategy that is beneficial in the online shopping scenario. Effective product bundling methods depend on high-quality item represe…

cs.AI2024★ 4 cited

MM-PhyRLHF: Reinforcement Learning Framework for Multimodal Physics Question-Answering

Janak Kapuriya, Chhavi Kirtani, Apoorv Singh +7

Recent advancements in LLMs have shown their significant potential in tasks like text summarization and generation. Yet, they often encounter difficulty while solving complex physi…