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
Masked Generative Policy for Robotic Control We present Masked Generative Policy (MGP), a novel framework for visuomotor imitation learning. We represent actions as discrete tokens, and train a conditional masked transformer that generates token... 6.50 0% See Reviews View AI Dashboard
Designing Observation and Action Models for Efficient Reinforcement Learning with LLMs The design of observation and action models is a fundamental step in reinforcement learning (RL), as it defines how agents perceive and interact with their environment. Despite its importance, this de... 4.80 26% See Reviews View AI Dashboard
Active Learning for Flow Matching Model in Shape Design: A Perspective from Continuous Condition Dataset Although the flow matching model has demonstrated powerful capabilities in modern machine learning, its training notoriously relies on an incredibly large scale of high-quality labeled samples. Nevert... 2.00 0% See Reviews View AI Dashboard
Hierarchical LLM-Guided Multi-Task Manipulation with Multimodal Learning and Action-Mask Policy Hierarchical policies that integrate high-level planning with low-level control have shown performance in robotic manipulation, but remain limited. We present a hierarchical framework that combin... 3.50 10% See Reviews View AI Dashboard
Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games Large Language Model (LLM) agents are reshaping the game industry, by enabling more intelligent and human-preferable characters. Yet, current game benchmarks fall short of practical needs: they lack e... 5.50 5% See Reviews View AI Dashboard
On the Reasoning Abilities of Masked Diffusion Language Models Masked diffusion models (MDMs) for text offer a compelling alternative to traditional autoregressive language models. Parallel generation makes them efficient, but their computational capabilities and... 7.00 0% See Reviews View AI Dashboard
KVCache-Centric Memory for LLM Agents LLM agents in complex, long-horizon workflows are constrained by the model’s context window. Current plaintext-based memory systems suffer from unstable retrieval accuracy and disrupt prefix caching, ... 4.67 31% See Reviews View AI Dashboard
Don't Run with Scissors: Pruning Breaks VLA Models but They Can Be Recovered Vision–Language–Action (VLA) models have advanced robotic capabilities but remain challenging to deploy on resource-limited hardware. Pruning has enabled efficient compression of large language models... 5.50 0% See Reviews View AI Dashboard
CodeMirage: Stress-Testing AI-Generated Code Detectors Against Production-Level LLMs Large language models (LLMs) are increasingly integrated into software development, generating substantial volumes of source code. While they enhance productivity, their misuse raises serious concerns... 4.00 5% See Reviews View AI Dashboard
Reinforced Data-Driven Estimation for Spectral Properties of Koopman Semigroup in Stochastic Dynamical Systems Analyzing the spectral properties of the Koopman operator is crucial for understanding and predicting the behavior of complex stochastic dynamical systems. However, the accuracy of data-driven estimat... 3.00 32% See Reviews View AI Dashboard
A superpersuasive autonomous policy debating system The capacity for complex, evidence-grounded, and strategically adaptive persuasion remains a formidable grand challenge for artificial intelligence. Prior work, like IBM Project Debater, focused on ge... 1.50 30% See Reviews View AI Dashboard
Invariant and equivariant architectures via learned polarization We present a theoretical framework for constructing invariant and equivariant neural network architectures based on polarization methods from classical invariant theory. Existing approaches to enfor... 2.00 0% See Reviews View AI Dashboard
QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL Designing and optimizing task-specific quantum circuits are crucial to leverage the advantage of quantum computing. Recent large language model (LLM)-based quantum circuit generation has emerged as a... 3.00 7% See Reviews View AI Dashboard
How Does Local Landscape Geometry Evolve in Language Model Pre-Training? The scale and expense of pre-training large language models make efficient hyperparameter tuning essential, yet principled guidance remains limited. To address this gap, we analyze language model pre-... 4.00 0% See Reviews View AI Dashboard
DRIP: Decompositional reasoning for Robust and Iterative Planning with LLM Agent Research on LLM agents has shown remarkable progress, particularly in planning methods that leverage the reasoning capabilities of LLMs. However, challenges such as robustness and efficiency remain in... 3.50 11% See Reviews View AI Dashboard
Navigating the Latent Space Dynamics of Neural Models Neural networks transform high-dimensional data into compact, structured representations, often modeled as elements of a lower dimensional latent space. In this paper, we present an alternative interp... 6.50 0% See Reviews View AI Dashboard
Planning at Inference: MCTS Test-Time Scaling for Long Video Generation Generating long videos with consistent content and visual quality remains a ma- jor challenge, as existing one-shot and chunked methods often suffer from se- mantic drift and compounding artifacts. We... 4.67 15% See Reviews View AI Dashboard
Identity-Preserving Human Reconstruction from a Single Image via Explicit 3D Reasoning We present the Identity-Preserving Large Human Reconstruction Model (IPRM), a feed-forward framework that reconstructs photorealistic, clothed 3D humans from a single in-the-wild image while preservin... 4.00 0% See Reviews View AI Dashboard
Rethinking CLIP for Long-Tailed Class-Incremental Learning Pre-trained vision–language models such as CLIP provide strong priors for class-incremental learning (CIL), yet existing methods degrade sharply in long-tailed scenarios. We demonstrate that CLIP, wi... 3.00 32% See Reviews View AI Dashboard
PISA: A Pragmatic Psych-Inspired Unified Memory System for Enhanced AI Agency Memory systems are fundamental to AI agents, yet existing work often lacks adaptability to diverse tasks and overlooks the constructive and task-oriented role of AI agent memory. Drawing from Piaget's... 3.00 12% See Reviews View AI Dashboard
SparseCodeQ: Extreme Sparse Coding Quantization for Large Vision-Language Models In this paper, we propose an extreme sparse coding quantization framework of 2-bit large vision-language models (LVLMs) for efficient multimodal reasoning. Conventional codebook-based quantization met... 4.00 0% See Reviews View AI Dashboard
Importance Sampling for Multi-Negative Multimodal Direct Preference Optimization Direct Preference Optimization (DPO) has recently been extended from text-only models to vision-language models. However, existing methods rely on oversimplified pairwise comparisons, generating a sin... 5.33 45% See Reviews View AI Dashboard
Expressive and Invariant Graph Learning via Canonical Tree Cover Neural Networks While message-passing NNs (MPNNs) are naturally invariant on graphs, they are fundamentally limited in expressive power. Canonicalization offers a powerful alternative by mapping each graph to a uniqu... 5.00 0% See Reviews View AI Dashboard
Omni-Weather: Unified Multimodal Foundation Model for Weather Generation and Understanding Weather modeling requires both accurate prediction and mechanistic interpretation, yet existing methods treat these goals in isolation, separating generation from understanding. To address this gap, w... 6.00 0% See Reviews View AI Dashboard
A Bootstrap Perspective on Stochastic Gradient Descent Machine learning models trained with stochastic gradient descent (SGD) can generalize better than those trained with deterministic gradient descent (GD). In this work, we study SGD's impact on general... 2.50 0% See Reviews View AI Dashboard
Tokenizing Single-Channel EEG with Time-Frequency Motif Learning Foundation models are reshaping EEG analysis, yet an important problem of EEG tokenization remains a challenge. This paper presents TFM-Tokenizer, a novel tokenization framework that learns a vocabul... 5.50 4% See Reviews View AI Dashboard
IncentRL: Bayesian Adaptation of Preference Gaps in Reinforcement Learning Reinforcement learning agents often struggle in sparse-reward settings, where intrinsic signals such as curiosity or empowerment are used to aid exploration. Existing approaches typically rely on fixe... 0.50 100% See Reviews View AI Dashboard
AFMCC: Asynchronous Federated Multi-modal Constrained Clustering Federated multi-modality clustering (FedMMC) aims to cluster distributed multi-modal data without compromising privacy. Existing approaches often rely on contrastive learning (CL), but suffer from rep... 3.00 57% See Reviews View AI Dashboard
A Neuro-symbolic Approach to Epistemic Deep Learning for Hierarchical Image Classification Deep neural networks achieve strong recognition performance, but they often produce overconfident predictions and fail to respect structural constraints in data. We propose a neuro-symbolic framework ... 1.50 41% See Reviews View AI Dashboard
Efficient LLM Collaboration via Planning Recently, large language models (LLMs) have demonstrated strong performance, ranging from simple to complex tasks. However, while large proprietary models (e.g., models with over 100B parameters) achi... 2.80 5% See Reviews View AI Dashboard
Bridging Gene Expression and Text: LLMs Can Complement Single-Cell Foundation Models Single-cell foundation models such as scGPT represent a significant advancement in single-cell omics, with an ability to achieve state-of-the-art performance on various downstream biological tasks. Ho... 3.50 0% See Reviews View AI Dashboard
DATR: DDI-Aware Therapeutic Structure Reconstruction for Safer Medication Recommendation Medication recommendation systems play a critical role in clinical decision support, where ensuring both predicting accuracy and safety, particularly drug-drug interaction (DDI) avoidance, is essentia... 4.67 17% See Reviews View AI Dashboard
Assumption-lean inference on treatment effect distributions In many fields, including healthcare, marketing, and online platform design, A/B tests are used to evaluate new treatments and make launch decisions based on average treatment effect (ATE) estimates. ... 3.50 0% See Reviews View AI Dashboard
Enhancing Diffusion-Based Sampling with Molecular Collective Variables Diffusion-based samplers learn to sample complex, high-dimensional distributions using energies or log densities alone, without training data. Yet, they remain impractical for molecular sampling becau... 6.50 0% See Reviews View AI Dashboard
ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Tasks Recent progress in large language models (LLMs) has enabled tool-augmented agents capable of solving complex real-world tasks through step-by-step reasoning. However, existing evaluations often focus ... 4.00 41% See Reviews View AI Dashboard
Silent Leaks: Implicit Knowledge Extraction Attack on RAG Systems Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by incorporating external knowledge bases, but this may expose them to extraction attacks, leading to potential copyri... 4.50 0% See Reviews View AI Dashboard
AnveshanaAI: A Multimodal Platform for Adaptive AI/ML Education Through Automated Question Generation and Interactive Assessment We propose AnveshanaAI, an application-based learning platform for artificial intelligence. With AnveshanaAI, learners are presented with a personalized dashboard featuring streaks, levels, badges, an... 1.50 100% See Reviews View AI Dashboard
Extrapolating Large Models from the Small: Optimal Learning of Scaling Laws Evaluating large language models (LLMs) is increasingly critical yet prohibitively expensive as models scale to billions of parameters. Predictive evaluation via scaling laws has emerged as a cost-eff... 4.00 4% See Reviews View AI Dashboard
Noise-Guided Transport for Imitation Learning We consider imitation learning in the low-data regime, where only a limited number of expert demonstrations are available. In this setting, methods that rely on large-scale pretraining or high-capacit... 3.50 0% See Reviews View AI Dashboard
OrtSAE: Orthogonal Sparse Autoencoders Uncover Atomic Features Sparse autoencoders (SAEs) are a technique for sparse decomposition of neural network activations into human-interpretable features. However, current SAEs suffer from feature absorption, where special... 6.00 9% See Reviews View AI Dashboard
How Many Code and Test Cases Are Enough? Evaluating Test Cases Generation from a Binary-Matrix Perspective Code evaluation and reinforcement learning rely critically on test cases. However, collecting golden test cases is hard and expensive, motivating the use of LLMs for automatic test case generation. Th... 6.00 10% See Reviews View AI Dashboard
From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shift Group-fairness metrics (e.g., equalized odds) can vary sharply across resamples and are especially brittle under distribution shift, undermining reliable audits. We propose a Wasserstein distributiona... 4.67 6% See Reviews View AI Dashboard
Weighted Deep Ensemble Under Misspecification Deep neural networks are supported by the universal approximation theorem, which guarantees that sufficiently large architectures can approximate smooth functions. In practice, however, this guarantee... 3.50 3% See Reviews View AI Dashboard
Decoupling Global Structure and Local Refinement: Blueprint-Guided Scroll Generation with Direct Preference Optimization Existing methods for generating long scroll images, often fail to maintain global structural and stylistic consistency, resulting in artifacts like content repetition. To address this, we propose the ... 3.00 20% See Reviews View AI Dashboard
O-Forge: An LLM + Computer Algebra Framework for Asymptotic Analysis Large language models have recently demonstrated advanced capabilities in solving IMO and Putnam problems; yet their role in research mathematics has remained fairly limited. The key difficulty is ver... 0.50 0% See Reviews View AI Dashboard
From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained Hypergradients Continual Learning (CL) aims to learn from a non-stationary data stream where the underlying distribution changes over time. While recent advances have produced efficient memory-free methods in the of... 4.00 0% See Reviews View AI Dashboard
Convergence dynamics of Agent-to-Agent Interactions with Misaligned objectives We develop a theoretical framework for agent-to-agent interactions in multi-agent scenarios. We consider the setup in which two language model based agents perform iterative gradient updates toward th... 5.00 10% See Reviews View AI Dashboard
Knowledge-enhanced MCTS for LLM-based Medical Diagnosis Reasoning Medical diagnosis is a high-stakes, knowledge-intensive task that requires precise reasoning over complex patient information. While Large Language Models (LLMs) have shown promise across a range of m... 3.50 38% See Reviews View AI Dashboard
A unified perspective on fine-tuning and sampling with diffusion and flow models We study the problem of training diffusion and flow generative models to sample from target distributions defined by an exponential tilting of the base density. This tasks subsumes sampling from unnor... 2.00 0% See Reviews View AI Dashboard
Learning to Undo: Transfer Reinforcement Learning under State Space Transformations Transfer learning in reinforcement learning (RL) has shown strong empirical success. In this work, we take a more principled perspective by studying when and how transferring knowledge between MDPs ca... 2.50 0% See Reviews View AI Dashboard
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