ICLR 2026 - Submissions

SubmissionsReviews

Submissions

Quantity AI Content: 0-10%10-30%30-50%50-70%70-90%90-100%All
Avg Rating: 0-11-22-33-44-55-66-77-88-99-10All

Summary Statistics

Quantity AI Content Count Avg Rating
0-10% 11864 (61%) 4.36
10-30% 3952 (20%) 4.14
30-50% 1846 (9%) 3.93
50-70% 1026 (5%) 3.75
70-90% 494 (3%) 3.39
90-100% 199 (1%) 2.90
Total 19490 (100%) 4.20
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
SynDoc: A Hybrid Discriminative-Generative Framework for Synthetic Domain-Adaptive Document Key Information Extraction Domain-specific Visually Rich Document Understanding (VRDU) presents significant challenges due to the complexity and sensitivity of documents in fields such as medicine, finance, and material science... 4.50 5% See Reviews View AI Dashboard
Distribution-Guided Expert Routing for Imbalanced Molecular Property Regression Molecular property regression often suffers from target distribution imbalance, where standard models tend to overfit to dense target regions and underperform on rare but critical ones. This limitatio... 3.00 36% See Reviews View AI Dashboard
Waven-Pull: Wavelet-based Anomaly Detection in Dynamic Graphs via Positive-Unlabeled Learning Anomaly detection in dynamic graphs is vital for identifying evolving threats in domains such as social networks and financial systems. While Graph Neural Networks (GNNs) have shown promise, they typi... 3.50 55% See Reviews View AI Dashboard
Adaptive Drug-Drug Interaction Prediction via Gauge-Aware Graph Representation and Distribution Alignment We re-study drug-drug interaction (DDI) prediction under the conditions of data scarcity and distribution shift. In this paper, we propose a practical framework that links a compact gauge-aware graph ... 1.50 20% See Reviews View AI Dashboard
Design Principles for TD-based Multi-Policy MORL in Infinite Horizons Multi-Objective Reinforcement Learning (MORL) addresses problems with multiple, often conflicting goals by seeking a set of trade-off policies rather than a single solution. Existing approaches that l... 2.50 0% See Reviews View AI Dashboard
Representational Alignment between Deep Neural Networks and Human Brain in Speech Processing under Audiovisual Noise Speech recognition in the human brain is an incremental process that begins with acoustic processing and advances to linguistic processing. While recent studies have revealed that the hierarchy of dee... 3.00 0% See Reviews View AI Dashboard
SaFT: Spotting Style Imitation and Filtering Content Interference for Zero-Shot LLM-Generated Text Detection Large language models (LLMs) have achieved advanced text generation capabilities, necessitating the development of reliable LLM-generated text detection to prevent potential misuse. However, current p... 4.00 22% See Reviews View AI Dashboard
iLRM: An Iterative Large 3D Reconstruction Model Feed-forward 3D modeling has emerged as a promising approach for rapid and high-quality 3D reconstruction. In particular, directly generating explicit 3D representations, such as 3D Gaussian splatting... 3.33 5% See Reviews View AI Dashboard
A Large-scale Dataset for Robust Complex Anime Scene Text Detection Current text detection datasets primarily target natural or document scenes, where text typically appear in regular font and shapes, monotonous colors, and orderly layouts. The text usually arranged a... 3.50 6% See Reviews View AI Dashboard
Differential Fine-Tuning Large Language Models Towards Better Diverse Reasoning Abilities Reasoning abilities of large language models (LLMs) require explicit derivations compared to general question-answering, supervised fine-tuning (SFT) can empower multiple reasoning abilities in LLMs v... 5.00 0% See Reviews View AI Dashboard
Flash-Mono: Feed-Forward Accelerated Gaussian Splatting Monocular SLAM Monocular 3D Gaussian Splatting SLAM suffers from critical limitations in time efficiency, geometric accuracy, and multi-view consistency. These issues stem from the time-consuming $\textit{Train-from... 5.00 5% See Reviews View AI Dashboard
AutoWeave: Automating Web Workflow Execution with Prompt-Adaptive Multi-Agent Orchestration Performing tasks automatically over the web using LLM-based agents has seen an emergent need and interest. Executing a web task based on the intent expressed by a user requires carrying out a sequence... 3.50 0% See Reviews View AI Dashboard
Accelerate Diffusion Transformers with Feature Momentum Diffusion models have demonstrated outstanding generative capabilities in image and video synthesis. However, their heavy computational burden, particularly due to the sequential denoising process and... 4.00 0% See Reviews View AI Dashboard
Read the Scene, Not the Script: Outcome-Aware Safety for LLMs Safety-aligned Large Language Models (LLMs) still show two dominant failure modes: they are easily jailbroken, or they over-refuse harmless inputs that contain sensitive surface signals. We trace both... 4.00 17% See Reviews View AI Dashboard
An Analysis of the Cauchy Method for Different Steplength Coefficient In this work we take the parameter r (recipprocal of optimal steplenth) as analysis target and introduce steplength coefficient t for classical steepest descent method for convex quadratic optimizatio... 0.50 0% See Reviews View AI Dashboard
Sublinear Time Quantum Sensitivity Sampling We present a unified framework for quantum sensitivity sampling, extending the advantages of quantum computing to a broad class of classical approximation problems. Our unified framework provides a st... 5.00 0% See Reviews View AI Dashboard
ActiveMark: on watermarking of visual foundation models via massive activations Being trained on large and vast datasets, visual foundation models (VFMs) can be fine-tuned for diverse downstream tasks, achieving remarkable performance and efficiency in various computer vision app... 2.67 0% See Reviews View AI Dashboard
SuperActivators: Transformers Concentrate Concept Signals in Just a Handful of Tokens Concept vectors aim to enhance model interpretability by linking internal representations with human-understandable semantics, but their utility is often limited by noisy and inconsistent activations.... 5.50 0% See Reviews View AI Dashboard
PRPO: Collaborative Online Policy Learning in Personalized RLHF Personalizing Large Language Models (LLMs) requires capturing user preferences without centralizing private data, prompting a multi-agent local fine-tuning setup. While on-policy algorithms, as applie... 3.50 0% See Reviews View AI Dashboard
Trajectory-Aware Verbalized Optimization for Multi-Agent Systems Large language model (LLM)-based multi-agent systems have shown significant potential, but their effectiveness often depends on manually engineered prompts, which are refined through labor-intensive t... 2.50 60% See Reviews View AI Dashboard
Counterfactual Structural Causal Bandits Causal reasoning lies at the heart of robust and generalizable decision-making, and the *Pearl Causal Hierarchy* provides a formal language for distinguishing between observational ($\mathcal{L}_1$), ... 5.50 0% See Reviews View AI Dashboard
SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms Rigorous testing of autonomous robots, such as self-driving vehicles, is essential to ensure their safety in real-world deployments. This requires building high-fidelity simulators to test scenarios b... 6.00 0% See Reviews View AI Dashboard
When to Use Which? An Investigation of Search Methods on Expensive Black-box Optimisation Problems Many real-world optimisation problems are black-box in the sense that the structure of their objective function is not accessible or exploitable. Some of such Black-Box Optimisation (BBO) problems are... 5.00 0% See Reviews View AI Dashboard
Variational Masked Diffusion Models Masked diffusion models have recently emerged as a flexible framework for discrete generative modeling. However, a key limitation of standard masked diffusion is its inability to effectively capture d... 4.00 0% See Reviews View AI Dashboard
FLEXITOKENS: Flexible Tokenization for Evolving Multilingual Language Models Multilingual language models are challenging to adapt to new data distributions by simple finetuning due to the rigidity of their subword tokenizers, which typically remain unchanged during adaptation... 3.00 0% See Reviews View AI Dashboard
Revisiting the Scaling Properties of Downstream Metrics in Large Language Model Training While scaling laws for Large Language Models (LLMs) traditionally focus on proxy metrics like pretraining loss, predicting downstream task performance has been considered unreliable. This paper challe... 6.00 6% See Reviews View AI Dashboard
Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation Diffusion models have achieved state-of-the-art performance in generating images, audio, and video, but their adaptation to text remains challenging due to its discrete nature. Prior approaches either... 4.50 0% See Reviews View AI Dashboard
Learning Ordinal Probabilistic Reward from Preferences Reward models are crucial for aligning large language models (LLMs) with human values and intentions. Existing approaches follow either Generative (GRMs) or Discriminative (DRMs) paradigms, yet both s... 5.00 0% See Reviews View AI Dashboard
Structured RAG for Answering Aggregative Questions Retrieval-Augmented Generation (RAG) has become the dominant approach for answering questions over large corpora. However, current datasets and methods are highly focused on cases where only a small p... 4.00 0% See Reviews View AI Dashboard
Data Pruning: Counting the Frequency of Loss Transition from Above-Average to Below-Average (FATB) During Early Training In this paper, we propose a novel data pruning algorithm named FATB, which aims to remove potentially redundant data and inherent noise in the original dataset during model training, thereby identifyi... 3.20 5% See Reviews View AI Dashboard
Harmonized Cone for Feasible and Non-conflict Directions in Training Physics-Informed Neural Networks Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving PDEs, yet training is difficult due to a multi-objective loss that couples PDE residuals, initial/boundary conditio... 6.00 8% See Reviews View AI Dashboard
Guided Domain Solver: Structured Exploration of Domain-Specific Tasks with Large Language Models This work presents a method to solve domain-specific problems by leveraging Monte Carlo Tree Search (MCTS), Knowledge Graphs and Large Language Model (LLM) agents. At the core of this approach lies a ... 1.60 5% See Reviews View AI Dashboard
Learning to Reason for Hallucination Span Detection Large language models (LLMs) often generate hallucinations---unsupported content that undermines reliability. While most prior works frame hallucination detection as a binary task, many real-world app... 5.50 18% See Reviews View AI Dashboard
Abnaolizer: An AI Agent for Converting Antibodies to Nanobodies Nanobodies, the naturally occurring single-chain antibodies derived from camelids, have emerged as highly promising therapeutic molecules due to their high stability, small size, and ease of engineeri... 1.33 22% See Reviews View AI Dashboard
Offline Policy Learning for Nonparametric Contextual Bandits under Relaxed Coverage This paper is concerned with learning an optimal policy in a nonparametric contextual bandit from offline, and possibly adaptively collected data. Existing methods and analyses typically rely on i.i.d... 5.00 0% See Reviews View AI Dashboard
GuardAlign: Robust Safety Alignment in Multimodal Large Language Models Multimodal large language models (MLLMs) have achieved remarkable progress in vision–language reasoning tasks, yet ensuring their safety remains a critical challenge. Recent input-side defenses detect... 5.50 18% See Reviews View AI Dashboard
Exploration Implies Data Augmentation: Generalisation in Contextual MDPs In the zero-shot policy transfer (ZSPT) setting for contextual Markov decision processes (MDP), agents train on a fixed set of contexts and must generalise to new ones. Recent work has argued and demo... 4.00 0% See Reviews View AI Dashboard
MedLesionVQA: A Multimodal Benchmark Emulating Clinical Visual Diagnosis for Body Surface Health Body-surface health conditions, spanning diverse clinical departments, represent some of the most frequent diagnostic scenarios and a primary target for medical multimodal large language models (MLLMs... 5.00 0% See Reviews View AI Dashboard
ROC-n-reroll: How verifier imperfection affects test-time scaling Test-time scaling aims to improve language model performance by leveraging additional compute during inference. Many works have empirically studied techniques such as Best-of-N (BoN) and Rejection Sa... 6.50 0% See Reviews View AI Dashboard
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Anti-Causal Model (SAM), a unifying causal framework that cha... 4.50 0% See Reviews View AI Dashboard
Learning to See Before Seeing: Demystifying LLM Visual Priors from Language Pre-training Large Language Models (LLMs), despite being trained on text alone, surprisingly develop rich visual priors. These priors allow latent visual capabilities to be unlocked for vision tasks with a relativ... 7.00 4% See Reviews View AI Dashboard
MindPilot: Closed-loop Visual Stimulation Optimization for Brain Modulation with EEG-guided Diffusion Whereas most brain–computer interface research has focused on decoding neural signals into behavior or intent, the reverse challenge—using controlled stimuli to steer brain activity—remains far less u... 5.50 24% See Reviews View AI Dashboard
A^2TG: Adaptive Anisotropic Textured Gaussians for Efficient 3D Scene Representation Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, exi... 5.50 7% See Reviews View AI Dashboard
DiffTrans: Differentiable Geometry-Materials Decomposition for Reconstructing Transparent Objects Reconstructing transparent objects from a set of multi-view images is a challenging task due to the complicated nature and indeterminate behavior of light propagation. Typical methods are primarily ta... 5.00 0% See Reviews View AI Dashboard
Generative Counterfactual Manifold Perturbation: A Robust Framework for Treatment Effect Estimation with Unobserved Confounders Estimating treatment effects from observational data is difficult when unobserved confounders create spurious associations that bias simple estimators. Recent generative approaches learn outcome distr... 2.67 38% See Reviews View AI Dashboard
Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models Log-likelihood evaluation enables important capabilities in generative models, including model comparison, certain fine-tuning objectives, and many downstream applications. Yet paradoxically, some of ... 4.50 4% See Reviews View AI Dashboard
GateFlow: Mitigating Shortcut Learning in VLA Models via Gated Flow Matching Vision-Language-Action (VLA) models promise general-purpose robotic intelligence by leveraging pretrained vision-language representations. However, these models suffer from shortcut learning—exploitin... 4.00 87% See Reviews View AI Dashboard
Multimodal Dataset Distillation via Phased Teacher Models Multimodal dataset distillation aims to construct compact synthetic datasets that enable efficient compression and knowledge transfer from large-scale image-text data. However, existing approaches oft... 4.50 7% See Reviews View AI Dashboard
MIRO: MultI-Reward cOnditioned pretraining improves T2I quality and efficiency Current text-to-image generative models are trained on large uncurated datasets to enable diverse generation capabilities. However, this does not align well with user preferences. Recently, reward mod... 4.50 43% See Reviews View AI Dashboard
Convergence of Muon with Newton-Schulz We analyze Muon as originally proposed and used in practice---using the momentum orthogonalization with a few Newton-Schulz steps. The prior theoretical results replace this key step in Muon with an e... 6.50 0% See Reviews View AI Dashboard
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