Cover Image

Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Simon, Panigrahi, Abhishek, Cheng, Yun, Yu, Dingli, Goyal, Anirudh, Arora, Sanjeev
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can Models Learn Skill Composition from Examples?
by: Zhao, Haoyu, et al.
Published: (2024)

Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning
by: Kaur, Simran, et al.
Published: (2024)

Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates
by: Lyu, Kaifeng, et al.
Published: (2024)

AdaptMI: Adaptive Skill-based In-context Math Instruction for Small Language Models
by: He, Yinghui, et al.
Published: (2025)

Trainable Transformer in Transformer
by: Panigrahi, Abhishek, et al.
Published: (2023)

Contextual Drag: How Errors in the Context Affect LLM Reasoning
by: Cheng, Yun, et al.
Published: (2026)

Escape the Language Prior: Mitigating Late-Stage Modality Collapse in Audio Reasoning via Modality-Aware Policy Optimization
by: Xiao, Cihan, et al.
Published: (2026)

Decompose, Look, and Reason: Reinforced Latent Reasoning for VLMs
by: Zhu, Mengdan, et al.
Published: (2026)

Self-Distillation Zero: Self-Revision Turns Binary Rewards into Dense Supervision
by: He, Yinghui, et al.
Published: (2026)

Can VLMs Recall Factual Associations From Visual References?
by: Ashok, Dhananjay, et al.
Published: (2025)

iVISPAR -- An Interactive Visual-Spatial Reasoning Benchmark for VLMs
by: Mayer, Julius, et al.
Published: (2025)

Can We Trust LLMs on Memristors? Diving into Reasoning Ability under Non-Ideality
by: Wu, Taiqiang, et al.
Published: (2026)

ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty
by: Wu, Xindi, et al.
Published: (2024)

Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs
by: Phukan, Anirudh, et al.
Published: (2024)

LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models
by: Arora, Abhishek, et al.
Published: (2023)

Can We Trust LLMs? Mitigate Overconfidence Bias in LLMs through Knowledge Transfer
by: Yang, Haoyan, et al.
Published: (2024)

Through the Lens of Contrast: Self-Improving Visual Reasoning in VLMs
by: Pan, Zhiyu, et al.
Published: (2026)

LLMs Can Evolve Continually on Modality for X-Modal Reasoning
by: Yu, Jiazuo, et al.
Published: (2024)

ASTRO: Teaching Language Models to Reason by Reflecting and Backtracking In-Context
by: Kim, Joongwon, et al.
Published: (2025)

Reasoning Robustness of LLMs to Adversarial Typographical Errors
by: Gan, Esther, et al.
Published: (2024)

Do Multilingual VLMs Reason Equally? A Cross-Lingual Visual Reasoning Audit for Indian Languages
by: R, Swastik
Published: (2026)

[De|Re]constructing VLMs' Reasoning in Counting
by: Alghisi, Simone, et al.
Published: (2025)

Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination
by: Shi, Chufan, et al.
Published: (2026)

When Big Models Train Small Ones: Label-Free Model Parity Alignment for Efficient Visual Question Answering using Small VLMs
by: Penamakuri, Abhirama Subramanyam, et al.
Published: (2025)

Can We Trust LLM Detectors?
by: Sandhan, Jivnesh, et al.
Published: (2026)

Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs
by: Carbune, Victor, et al.
Published: (2024)

Do LLMs and VLMs Share Neurons for Inference? Evidence and Mechanisms of Cross-Modal Transfer
by: Cui, Chenhang, et al.
Published: (2026)

MMGR: Multi-Modal Generative Reasoning
by: Cai, Zefan, et al.
Published: (2025)

Representing Rule-based Chatbots with Transformers
by: Friedman, Dan, et al.
Published: (2024)

Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better
by: Wang, Dianyi, et al.
Published: (2025)

Mitigating Data Imbalance in Automated Speaking Assessment
by: Tsai, Fong-Chun, et al.
Published: (2025)

VLMs Can Aggregate Scattered Training Patches
by: Zhou, Zhanhui, et al.
Published: (2025)

Flattery, Fluff, and Fog: Diagnosing and Mitigating Idiosyncratic Biases in Preference Models
by: Bharadwaj, Anirudh, et al.
Published: (2025)

Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs
by: Shen, Yifan, et al.
Published: (2025)

Improving Sparse Memory Finetuning
by: Goyal, Satyam, et al.
Published: (2026)

Sparse Memory Finetuning as a Low-Forgetting Alternative to LoRA and Full Finetuning
by: Gupta, Prakhar, et al.
Published: (2026)

Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
by: Zhao, Yiran, et al.
Published: (2024)

Do Text Edits Generalize to Visual Generation? Benchmarking Cross-Modal Knowledge Editing in UMMs
by: Gao, Xin, et al.
Published: (2026)

How Far Are We from Intelligent Visual Deductive Reasoning?
by: Zhang, Yizhe, et al.
Published: (2024)

Comparing Importance Sampling Based Methods for Mitigating the Effect of Class Imbalance
by: Panigrahi, Indu, et al.
Published: (2024)