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
CoLaP: Contrastive Learning with Adaptive Prompts for Continual Learning Continual learning (CL) aims to enable models to learn a sequence of new tasks without forgetting previously acquired knowledge. Prompt-based approaches, which adapt small prompt parameters while keep... 2.00 13% See Reviews View AI Dashboard
Teaching LLMs to Plan: Logical Chain-of-Thought Instruction Tuning for Symbolic Planning Large language models (LLMs) have demonstrated impressive capabilities across diverse tasks, yet their ability to perform structured symbolic planning remains limited, particularly in domains requirin... 4.50 27% See Reviews View AI Dashboard
HT-Transformer: Event Sequences Classification by Accumulating Prefix Information with History Tokens Deep learning has achieved strong results in modeling sequential data, including event sequences, temporal point processes, and irregular time series. Recently, transformers have largely replaced recu... 2.40 11% See Reviews View AI Dashboard
3DPhysVideo: 3D Scene Reconstruction and Physical Animation Leveraging a Video Generation Model via Consistency-Guided Flow SDE Video generative models have made remarkable progress, yet they often yield visual artifacts that violate grounding in real-world physical dynamics. Recent works such as PhysGen3D tackle single image-... 5.00 3% See Reviews View AI Dashboard
Latency-Aware Contextual Bandit: Application to Cryo-EM Data Collection We introduce a latency-aware contextual bandit framework that generalizes the standard contextual bandit problem, where the learner adaptively selects arms and switches decision sets under action dela... 4.00 14% See Reviews View AI Dashboard
TheMCPCompany: Creating General-purpose Agents with Task-specific Tools Since the introduction of the Model Context Protocol (MCP), the number of available tools for Large Language Models (LLMs) has increased significantly. These task-specific tool sets offer an alternati... 5.00 0% See Reviews View AI Dashboard
WAVE: Learning Unified & Versatile Audio-Visual Embeddings with Multimodal LLM While embeddings from multimodal large language models (LLMs) excel as general-purpose representations, their application to dynamic modalities like audio and video remains underexplored. We introduce... 6.00 12% See Reviews View AI Dashboard
CAP: Improving the Robustness of LLM-as-a-Judge Against Adversarial Score Manipulation via Comparative Augmented Prompting Large language models (LLMs) have been widely adopted in automated evaluation tasks, demonstrating human-aligned assessment capabilities. However, studies reveal that LLM-as-a-Judge systems exhibit si... 3.33 7% See Reviews View AI Dashboard
Structuring Hidden Features via Clustering of Unit-Level Activation Patterns We propose a self-supervised learning framework that organizes hidden feature representations across layers, thereby enhancing interpretability. The framework first discovers unit-level structures by ... 3.33 21% See Reviews View AI Dashboard
variCOT: Variational Inference for Implicit Chain-of-Thought in Language Models Chain-of-Thought (CoT) reasoning dramatically improves language model performance but incurs significant computational overhead through sequential token generation. While implicit CoT methods promise ... 2.50 80% See Reviews View AI Dashboard
Holistic Prompting: Joint Reasoning with Reusable States and Shortcut Discovery Large Language Models (LLMs) have demonstrated significant capabilities in complex reasoning tasks, often employing frameworks like Tree of Thoughts (ToT) and Chain-of-Thought (CoT). However, such me... 3.50 0% See Reviews View AI Dashboard
Fair Graph Machine Learning under Adversarial Missingness Processes Graph Neural Networks (GNNs) have achieved state-of-the-art results in many relevant tasks where decisions might disproportionately impact specific communities. However, existing work on fair GNNs oft... 5.33 0% See Reviews View AI Dashboard
Hierarchical Speculative Decoding through Training-Free Slim-Verifier Speculative decoding (SD) addresses the high inference costs of large language models by having lightweight drafters generate candidates for large verifiers to validate in parallel. Current draft-ver... 2.67 22% See Reviews View AI Dashboard
Single-Step Bidirectional Unpaired Image Translation Using Implicit Bridge Consistency Distillation Unpaired image-to-image translation has seen significant progress since the introduction of CycleGAN. However, methods based on diffusion models or Schrödinger bridges have yet to be widely adopted in... 5.00 0% See Reviews View AI Dashboard
Fundamental bounds on efficiency-confidence trade-off for transductive conformal prediction Transductive conformal prediction addresses the simultaneous prediction for multiple data points. Given a desired confidence level, the objective is to construct a prediction set that includes the tru... 5.00 5% See Reviews View AI Dashboard
Nested Hash Layer: A Plug-and-play Module for Multiple-length Hash Code Learning Deep supervised hashing is essential for efficient storage and search in large-scale image retrieval. Traditional models generate hash codes of a single length, but this creates a trade-off between ef... 3.50 0% See Reviews View AI Dashboard
Dynamic Experts Search: Enhancing Reasoning in Mixture-of-Experts LLMs at Test Time Test-Time Scaling (TTS) enhances the reasoning ability of large language models (LLMs) by allocating additional computation during inference. However, existing approaches primarily rely on output-leve... 4.00 4% See Reviews View AI Dashboard
Style2Shape: Image Style Guided 3D Shape Material Generation This paper presents Style2Shape, a novel framework for generating physically-based rendering (PBR) materials for 3D models from a single reference image. Unlike existing methods limited by the diversi... 3.50 84% See Reviews View AI Dashboard
Automating the Refinement of Reinforcement Learning Specifications Logical specifications have been shown to help reinforcement learning algorithms in achieving complex tasks. However, when a task is under-specified, agents might fail to learn useful policies. In thi... 5.50 25% See Reviews View AI Dashboard
STDDN: A Physics-Guided Deep Learning Framework for Crowd Simulation Accurate crowd simulation is crucial for public safety management, emergency evacuation planning, and intelligent transportation systems. However, existing methods, which typically model crowds as a c... 6.00 19% See Reviews View AI Dashboard
ACON: Optimizing Context Compression for Long-horizon LLM Agents Large language models (LLMs) are increasingly deployed as agents in dynamic, real-world environments, where success requires both reasoning and effective tool use. A central challenge for agentic task... 4.00 4% See Reviews View AI Dashboard
Learning Part-Aware Dense 3D Feature Field For Generalizable Articulated Object Manipulation Articulated object manipulation is essential for various real-world robotic tasks, yet generalizing across diverse objects remains a major challenge. A key to generalization lies in understanding func... 6.00 0% See Reviews View AI Dashboard
Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation Vision language models (VLMs) often generate hallucination, i.e., content that cannot be substantiated by either textual or visual inputs. Prior work primarily attributes this to over-reliance on ling... 4.00 4% See Reviews View AI Dashboard
Rethinking the Value of Multi-Agent Workflow: A Strong Single Agent Baseline Recent advances in LLM-based multi-agent systems (MAS) show that workflows composed of multiple LLM agents with distinct roles, tools, and communication patterns can outperform single-LLM baselines on... 4.50 33% See Reviews View AI Dashboard
TusoAI: Agentic Optimization for Scientific Methods Scientific discovery is often slowed by the manual development of computational tools needed to analyze complex experimental data. Building such tools is costly and time-consuming because scientists m... 3.60 0% See Reviews View AI Dashboard
One Bad Sample May Spoil the Whole Batch: A Novel Backdoor-Like Attack Towards Large Batch Processing As hardware accelerators like TPUs and large-memory GPUs continue to evolve rapidly, an increasing number of Artificial Intelligence (AI) applications are utilizing extremely large batch sizes to acce... 4.67 0% See Reviews View AI Dashboard
DERMARK: A Dynamic, Efficient and Robust Multi-bit Watermark for Large Language Models As large language models (LLMs) grow more powerful, concerns over copyright infringement of LLM-generated texts have intensified. LLM watermarking has been proposed to trace unauthorized redistributio... 4.50 9% See Reviews View AI Dashboard
KineDiff3D: Kinematic-Aware Diffusion for Category-Level Articulated Object Shape Reconstruction and Generation Articulated objects, such as laptops and drawers, exhibit significant challenges for 3D reconstruction and pose estimation due to their multi-part geometries and variable joint configurations, which i... 3.00 51% See Reviews View AI Dashboard
Guaranteeing Conservation of Integrals with Projection in Physics-Informed Neural Networks We propose a novel projection method that guarantees the conservation of integral quantities in Physics-Informed Neural Networks (PINNs). While the soft constraint PINNs use to enforce the structure o... 2.50 0% See Reviews View AI Dashboard
Personalization Under Value Conflict: Resolving Contradictory Preferences with Paired Fine-Tuning Large language models (LLMs) are increasingly expected to capture not only broadly shared human universal values but also the diverse and often contradictory preferences of individual users. Existing ... 3.00 24% See Reviews View AI Dashboard
SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models Diffusion large language models (dLLMs) are emerging as an efficient alternative to autoregressive models due to their ability to decode multiple tokens in parallel. However, aligning dLLMs with human... 5.00 4% See Reviews View AI Dashboard
EmotionThinker: Prosody-Aware Reinforcement Learning for Explainable Speech Emotion Reasoning Emotional information in speech plays a unique role in multimodal perception. However, current Speech Large Language Models (SpeechLLMs), similar to conventional speech emotion recognition (SER) syste... 6.50 13% See Reviews View AI Dashboard
TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models Existing medical reasoning benchmarks for vision-language models primarily focus on analyzing a patient's condition based on an image from a *single* visit. However, this setting deviates significantl... 4.00 0% See Reviews View AI Dashboard
Rotation Control Unlearning: Quantifying and Controlling Continuous Unlearning for LLM with The Cognitive Rotation Space As Large Language Models (LLMs) become increasingly prevalent, their security vulnerabilities have already drawn attention. Machine unlearning is introduced to seek to mitigate these risks by removing... 4.00 0% See Reviews View AI Dashboard
Latent Planning Emerges with Scale LLMs can perform seemingly planning-intensive tasks, like writing coherent stories or functioning code, without explicitly verbalizing a plan; however, the extent to which they implicitly plan is unkn... 5.33 0% See Reviews View AI Dashboard
Knowledge distillation through geometry-aware representational alignment Knowledge distillation is a common paradigm for transferring capabilities from larger models to smaller ones. While traditional distillation methods leverage a probabilistic divergence over the output... 4.00 0% See Reviews View AI Dashboard
Uncertainty‑Routed Human–LLM Curation and Calibration for ANLI Adversarial NLI (ANLI) reveals distribution-shift failures that static benchmarks miss, motivating evaluation and curation that are explicitly uncertainty-aware. We present URC2—Uncertainty-Routed Cur... 2.00 34% See Reviews View AI Dashboard
Controlling a $\mu$RTS agent using Decision Transformers Decision Transformers (DT) are a Return-Conditioned Supervised Learning (RCSL) technique. A DT policy predicts actions by attending to a limited history of tokens that encodes states, actions and retu... 2.00 0% See Reviews View AI Dashboard
Can Text-to-Video Models Generate Realistic Human Motion? Recent advances in text-to-video (T2V) generation have yielded impressive progress in resolution, duration, and prompt fidelity, with models such as Pika, Gen-3, and Sora producing clips that appear c... 4.50 53% See Reviews View AI Dashboard
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts Large language models (LLMs) have achieved remarkable progress, with Parameter-Efficient Fine-Tuning (PEFT) emerging as a key technique for downstream task adaptation. However, existing PEFT methods m... 4.00 18% See Reviews View AI Dashboard
QuRL: Rubrics As Judge For Open-Ended Question Answering Reinforcement Learning from Verifiable Rewards (RLVR) has significantly improved the performance of large language models (LLMs) on tasks with gold ground truth, such as code generation and mathematic... 5.33 13% See Reviews View AI Dashboard
Improved Sample Complexity Bounds For Diffusion Model Training Without Empirical Risk Minimizer Access Diffusion models have demonstrated remarkable performance in generating high-dimensional samples across domains such as vision, language, and the sciences. Although continuous-state diffusion models h... 3.50 0% See Reviews View AI Dashboard
SCMF: Lightweight Retrieval-Augmented Generation via Retrieval Vector Compression With the widespread adoption of Retrieval-Augmented Generation (RAG) in knowledge-intensive tasks, efficiency bottlenecks become increasingly evident: storing and retrieving large-scale high-dimension... 2.00 60% See Reviews View AI Dashboard
Minimum-Excess-Work Guidance We propose a regularization framework inspired by thermodynamic work for guiding pre-trained probability flow generative models (e.g., continuous normalizing flows or diffusion models) by minimizing e... 4.50 7% See Reviews View AI Dashboard
Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models Counterfactual generation aims to simulate realistic hypothetical outcomes under causal interventions. Diffusion models have emerged as a powerful tool for this task, combining DDIM inversion with con... 3.50 10% See Reviews View AI Dashboard
ParaS2S: Benchmarking and Aligning Spoken Language Models for Paralinguistic-aware Speech-to-Speech Interaction Speech-to-Speech (S2S) models have shown promising dialogue capabilities, but their ability to handle paralinguistic cues—such as emotion, tone, and speaker attributes—and to respond appropriately in ... 5.50 0% See Reviews View AI Dashboard
ChemReason: A Chemical Code-Driven Reasoning LLM via Verifiable Reinforcement Learning In chemistry, most research on large language models has centered on knowledge question answering and retrieval. However, these approaches fall short on core tasks such as open molecular generation an... 2.00 7% See Reviews View AI Dashboard
United Minds or Isolated Agents? Exploring Coordination of LLMs under Cognitive Load Theory Large Language Models (LLMs) exhibit a notable performance ceiling on complex, multi-faceted tasks, as they often fail to integrate diverse information or adhere to multiple constraints. We posit... 4.50 50% See Reviews View AI Dashboard
Not All Clients Are Equal: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients As AI becomes more personal, e.g., Agentic AI, there is an increasing need for personalizing models for various use cases. Personalized federated learning (PFL) enables each client to collaboratively ... 7.00 0% See Reviews View AI Dashboard
Fairness Aware Reward Optimization LLMs are typically aligned with human feedback via reward models but demographic skews and group-dependent disagreements in annotations can propagate systematic unfairness. We introduce Fairness-Aware... 3.00 4% See Reviews View AI Dashboard
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