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
Forge: Foundational Optimization Representations from Graph Embeddings Combinatorial optimization problems are ubiquitous in science and engineering. Still, learning-based approaches to accelerate combinatorial optimization often require solving a large number of difficu... 5.00 0% See Reviews View AI Dashboard
StepORLM: A Self-Evolving Framework With Generative Process Supervision For Operations Research Language Models Large Language Models (LLMs) have shown promising capabilities for solving Operations Research (OR) problems. While reinforcement learning serves as a powerful paradigm for LLM training on OR problem... 5.00 17% See Reviews View AI Dashboard
Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion Existing diffusion-based time series forecasting methods often target on mixed temporal patterns or undifferentiated residuals, limiting the potential of distinct temporal components. In this paper, w... 4.00 0% See Reviews View AI Dashboard
Nonparametric Teaching for Sequential Property Learners Determining the properties of sequence-structured data, e.g., the sentiment of a text, fundamentally requires learning the implicit relationship that maps sequences to their corresponding properties. ... 3.00 0% See Reviews View AI Dashboard
FG-ATTN: LEVERAGING FINE-GRAINED SPARSITY IN DIFFUSION TRANSFORMERS Generating realistic videos/images with diffusion transformers requires evaluating attention over extremely long sequences, with attention layers accounting for the majority of generation latency. Exp... 4.00 0% See Reviews View AI Dashboard
LSMSeg: Unleashing the Power of Large-Scale Models for Open-Vocabulary Semantic Segmentation Open-vocabulary semantic segmentation requires precise pixel-level alignment of visual and textual representations, leveraging text as a universal reference to address visual disparities across divers... 3.50 0% See Reviews View AI Dashboard
Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift Time-series forecasting finds broad applications in real-world scenarios. Due to the dynamic nature of time series data, it is important for time-series forecasting models to handle potential distribu... 6.00 0% See Reviews View AI Dashboard
SAFE: Improving LLM Systems using Sentence-Level In-generation Attribution Large Language Models (LLMs) are increasingly applied in various science domains, yet their broader adoption remains constrained by a critical challenge: the lack of trustworthy, verifiable outputs. C... 1.50 0% See Reviews View AI Dashboard
SCREEN-SBERT: EMBEDDING FUNCTIONAL SEMANTICS OF GUI SCREENS TO SUPPORT GUI AGENTS Recent GUI agent studies show that augmenting LLM prompts with app-related knowledge constructed during a pre-exploration phase can effectively improve task success rates. However, retrieving relevant... 5.50 0% See Reviews View AI Dashboard
Model Merging with Functional Dual Anchors Model merging is an efficient post-training strategy for integrating knowledge from multiple finetuned checkpoints of a shared foundation model. Existing methods operate in the parameter space, combin... 4.50 0% See Reviews View AI Dashboard
Kimi-Dev: Agentless Training as Skill Prior for SWE-agents Large Language Models (LLMs) are increasingly applied to software engineering (SWE), with SWE-bench as a key benchmark. Solutions are split into SWE-Agent frameworks with multi-turn interactions and w... 7.00 0% See Reviews View AI Dashboard
Fast, Secure, And High-Capacity Image Watermarking With Text Autoencoded Text Vectors Most image watermarking systems focus on robustness, capacity, and imperceptibility while treating the embedded payload as meaningless bits. This bit-centric view imposes a hard ceiling on capacity an... 4.67 0% See Reviews View AI Dashboard
C3-OWD: A Curriculum Cross-modal Contrastive Learning Framework for Open-World Detection Object detection has advanced significantly in the closed-set setting, but real-world deployment remains limited by two challenges: poor generalization to unseen categories and insufficient robustness... 4.50 53% See Reviews View AI Dashboard
Pretrain–Test Task Alignment Governs Generalization in In-Context Learning In-context learning (ICL) is a central capability of Transformer models, but the structures in data that enable its emergence and govern its robustness remain poorly understood. In this work, we study... 6.00 0% See Reviews View AI Dashboard
SimTrack3D: A Simple Sequential Motion Modeling for Efficient 3D Single Object Tracking Accurate tracking of objects in 3D point clouds requires continuous and efficient motion modeling across spatial and temporal dimensions. Although voxel-based methods have recently achieved strong per... 3.50 5% See Reviews View AI Dashboard
Preference Learning from Physics-Based Feedback: Tuning Language Models to Design BCC/B2 Superalloys We apply preference learning to the task of language model generation of novel structural alloys. Where prior work focuses on generating stable inorganic crystals, our approach optimizes for the synth... 3.00 0% See Reviews View AI Dashboard
SoundReactor: Frame-level Online Video-to-Audio Generation Prevailing Video-to-Audio (V2A) generation models operate offline, assuming an entire video sequence or chunks of frames are available beforehand. This critically limits their use in interactive appli... 4.00 0% See Reviews View AI Dashboard
Conformalized Predictions in Hypergraph Neural Networks via Contrastive Learning Hypergraph representation learning has gained immense popularity over the last few years due to its applications in real-world domains like social network analysis, recommendation systems, biological ... 5.33 12% See Reviews View AI Dashboard
On the Limits of Sparse Autoencoders: A Theoretical Framework and Reweighted Remedy Sparse autoencoders (SAEs) have recently emerged as a powerful tool for interpreting the features learned by large language models (LLMs). By reconstructing features with sparsely activated networks, ... 6.00 0% See Reviews View AI Dashboard
Wasserstein Policy Gradient: Implicit Policies, Entropy Regularization and Linear Convergence We revisit Wasserstein Proximal Policy Gradient (WPPG) for continuous control in infinite-horizon discounted reinforcement learning. By projecting the iterate of Wasserstein proximal gradient onto a p... 5.00 3% See Reviews View AI Dashboard
SPEAR: A Unified SSL Framework for Learning Speech and Audio Representations Self-Supervised Learning (SSL) excels at learning generic representations of acoustic signals, yet prevailing methods remain domain-specific, tailored to either speech or general audio, hindering the ... 5.00 0% See Reviews View AI Dashboard
VELR: Efficient Video Reward Feedback via Ensemble Latent Reward Models Reward feedback learning (ReFL) is effective for both text-to-image (T2I) and text-to-video (T2V) generation with image reward models (RMs). However, image RMs are misaligned with temporal objectives ... 4.67 58% See Reviews View AI Dashboard
GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials 3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but it predominantly targ... 4.50 0% See Reviews View AI Dashboard
The Matthew Effect of AI Programming Assistants: A Hidden Bias in Software Evolution AI-assisted programming is rapidly reshaping software development, with large language models (LLMs) enabling new paradigms such as vibe coding and agentic coding. While prior works have focused on pr... 4.40 72% See Reviews View AI Dashboard
Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation The rapid advancement of video diffusion models has been hindered by fundamental limitations in temporal modeling, particularly the rigid synchronization of frame evolution imposed by conventional sca... 6.00 13% See Reviews View AI Dashboard
VeriRole: Verifiable Role-Awareness through Hint-Guided Reinforcement Learning Maintaining role-awareness in Role-Playing Conversational Agents (RPCAs) is a significant challenging, largely because the creative nature of role-playing makes it difficult to design verifiable rewar... 5.50 10% See Reviews View AI Dashboard
Training-Free Self-Scheduling for Efficient LLM Inference Serving The ability to deliver fast responses under strict latency requirements is critical for Large Language Model (LLM) inference serving. Most existing systems rely on a first-come-first-served (FCFS) sc... 3.60 25% See Reviews View AI Dashboard
Mixed-Curvature Tree-Sliced Wasserstein Distance Mixed-curvature spaces have emerged as a powerful alternative to their Euclidean counterpart, enabling data representations better aligned with the intrinsic structure of complex datasets. However, co... 6.00 21% See Reviews View AI Dashboard
Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking Test-time algorithms that combine the *generative* power of language models with *process verifiers* that assess the quality of partial generations offer a promising lever for eliciting new reasoning ... 6.50 0% See Reviews View AI Dashboard
Sparsity-promoting Fine-tuning for Equivariant Materials Foundation Model Pre-trained materials foundation models, or machine learning interatomic potentials, leverage general physicochemical knowledge to effectively approximate potential energy surfaces. However, they ofte... 4.50 3% See Reviews View AI Dashboard
Concept-Based Steering of LLMs for Conditional Molecular Generation Generating valid, unique, and high-fidelity molecules while precisely controlling for multiple properties simultaneously remains challenging. While prior works with LLMs have achieved success by fine-... 3.33 5% See Reviews View AI Dashboard
Variational Learning of Disentangled Representations Disentangled representations allow models to separate factors shared across conditions from those that are condition-specific. This separation is crucial in domains such as biomedicine, where generali... 4.00 0% See Reviews View AI Dashboard
Local Distribution-Conditioned Image Synthesis for One-Shot Federated Learning One-Shot Federated Learning (OSFL) aims to build a global model with a single round of server–client interaction, making it attractive for practical scenarios. The recent introduction of Diffusion Mod... 4.00 8% See Reviews View AI Dashboard
ReAlign: Safety-Aligning Reasoning Models with Verifier-Guided Reinforcement Learning As Large Reasoning Models (LRMs) become more capable, ensuring their safety without compromising utility is a critical challenge. Traditional safety alignment techniques often result in overly cautiou... 3.50 13% See Reviews View AI Dashboard
Do Vision-Language Models Respect Contextual Integrity in Location Disclosure? Vision-language models (VLMs) have recently demonstrated strong performance in image geolocation, identifying images' location to a precision that now surpasses specialized systems. This capability po... 5.50 0% See Reviews View AI Dashboard
How reinforcement learning after next-token prediction facilitates learning Recent advances in reasoning domains with neural networks have primarily been enabled by a training recipe that optimizes Large Language Models, previously trained to predict the next-token in a seque... 6.00 0% See Reviews View AI Dashboard
Poly-FEVER: A Multilingual Fact Verification Benchmark for Hallucination Detection in Large Language Models We present Poly-FEVER, a large-scale multilingual benchmark for fact verification and hallucination detection in large language models (LLMs). Poly-FEVER extends FEVER, Climate-FEVER, and SciFact to 7... 5.00 45% See Reviews View AI Dashboard
WebGen-R1: Incentivizing LLMs to Generate Functional and Aesthetic Websites with Reinforcement Learning Large Language Models (LLMs) have demonstrated strong capabilities in functional-level code generation, yet their performance remains limited in project-level scenarios such as generating large-scale ... 5.00 51% See Reviews View AI Dashboard
Dolphin: A multimodal large language model for Ultrasound Understanding Ultrasound is one of the most widely used imaging modalities in clinical practice. Unlike CT and MRI, ultrasound imaging is highly operator dependent, with significant variations across different anat... 4.50 26% See Reviews View AI Dashboard
Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking Improving vision-language models (VLM) in the post-training stage typically relies on supervised fine-tuning or reinforcement learning, methods that necessitate costly, human-annotated data. While se... 5.00 10% See Reviews View AI Dashboard
Learning Communication between Language Models through Dense Vectors Communication between language models plays a crucial role in the inference process of large language models (LLMs), occurring both iteratively within a single model for multi-step reasoning (auto-reg... 3.50 0% See Reviews View AI Dashboard
Consistent Labeling Across Group Assignments: Variance Reduction in Conditional Average Treatment Effect Estimation Numerous algorithms have been developed for Conditional Average Treatment Effect (CATE) estimation. In this paper, we first highlight an overlooked issue in CATE estimation: many algorithms exhibit in... 2.50 19% See Reviews View AI Dashboard
LATTE: Latent Trajectory Embedding for Diffusion-Generated Image Detection The rapid advancement of diffusion-based image generators has made it increasingly difficult to distinguish generated from real images. This erodes trust in digital media, making it critical to develo... 2.50 15% See Reviews View AI Dashboard
MSRS: Adaptive Multi-Subspace Representation Steering for Attribute Alignment in Large Language Models Activation steering offers a promising approach to controlling the behavior of Large Language Models by directly manipulating their internal activations. However, most existing methods struggle to joi... 4.50 27% See Reviews View AI Dashboard
3DLAND: 3D Lesion Abdominal anomaly Localization Dataset Existing medical imaging datasets for abdominal CT often lack three-dimensional annotations, multi-organ coverage, or precise lesion-to-organ associations, hindering robust representation learning and... 5.00 76% See Reviews View AI Dashboard
DefNTaxS: The Inevitable Need for Context in Classification To successfully use generalized vision-language models (VLMs) like CLIP for zero-shot image classification, the semantics of the target classes must be well defined and easily differentiated. However,... 3.00 30% See Reviews View AI Dashboard
EditScore: Unlocking Online RL for Image Editing via High-Fidelity Reward Modeling Instruction-guided image editing has achieved remarkable progress, yet current models still face challenges with complex instructions and often require multiple samples to produce a desired result. Re... 5.00 0% See Reviews View AI Dashboard
Judo: A Juxtaposed Domain-oriented Multimodal Reasoner for Industrial Anomaly QA Industrial anomaly detection has been significantly advanced by large multimodal models (LMMs), enabling diverse human instructions beyond detection, particularly through visual-grounded reasoning for... 4.50 0% See Reviews View AI Dashboard
Lifelong control through Neuro-Evolution Reinforcement learning (RL) under continual environmental changes has remained a central challenge for decades. Novel designs of loss functions, training procedures and neural network architectures ha... 3.20 12% See Reviews View AI Dashboard
R2Q: Residual Refinement Quantization for Robust 2-Bit Large Language Models The dramatic growth of Large Language Models (LLMs) has been accompanied by significant computational and memory demands, driving the adoption of low-bit quantization. While 8-bit and 4-bit formats ha... 2.00 14% See Reviews View AI Dashboard
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