title stringlengths 15 138 | url stringlengths 42 42 | detail_url stringlengths 42 42 | authors stringlengths 7 526 | tags stringclasses 3
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BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity | https://openreview.net/forum?id=mQYHXUUTkU | https://openreview.net/forum?id=mQYHXUUTkU | Andrew Luo,Margaret Marie Henderson,Michael J. Tarr,Leila Wehbe | ICLR 2024,Poster | Understanding the functional organization of higher visual cortex is a central focus in neuroscience. Past studies have primarily mapped the visual and semantic selectivity of neural populations using hand-selected stimuli, which may potentially bias results towards pre-existing hypotheses of visual cortex functionalit... | https://openreview.net/pdf/a709ed572ed6c4b00439d924d8b85931fc309202.pdf |
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion | https://openreview.net/forum?id=FvK2noilxT | https://openreview.net/forum?id=FvK2noilxT | Xueyi Liu,Li Yi | ICLR 2024,Poster | In this work, we tackle the challenging problem of denoising hand-object interactions (HOI). Given an erroneous interaction sequence, the objective is to refine the incorrect hand trajectory to remove interaction artifacts for a perceptually realistic sequence. This challenge involves intricate interaction noise, incl... | https://openreview.net/pdf/758b44508c97b8e9709281ba88fb4e1cc4c92077.pdf |
Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models | https://openreview.net/forum?id=zpVPhvVKXk | https://openreview.net/forum?id=zpVPhvVKXk | Senmao Li,Joost van de Weijer,taihang Hu,Fahad Khan,Qibin Hou,Yaxing Wang,jian Yang | ICLR 2024,Poster | The success of recent text-to-image diffusion models is largely due to their capacity to be guided by a complex text prompt, which enables users to precisely describe the desired content. However, these models struggle to effectively suppress the generation of undesired content, which is explicitly requested to be omit... | https://openreview.net/pdf/9aee144b4a2835b09f6d4e543e1b219cbbd1ebc6.pdf |
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation | https://openreview.net/forum?id=OZitfSXpdT | https://openreview.net/forum?id=OZitfSXpdT | Chengming Hu,Haolun Wu,Xuan Li,Chen Ma,Xi Chen,Boyu Wang,Jun Yan,Xue Liu | ICLR 2024,Poster | Knowledge distillation aims to train a compact student network using soft supervision from a larger teacher network and hard supervision from ground truths. However, determining an optimal knowledge fusion ratio that balances these supervisory signals remains challenging. Prior methods generally resort to a constant or... | https://openreview.net/pdf/1ff49fb0c880655936d929769c3a595b46f08d38.pdf |
Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space | https://openreview.net/forum?id=CEkIyshNbC | https://openreview.net/forum?id=CEkIyshNbC | Yufei Gu,Xiaoqing Zheng,Tomaso Aste | ICLR 2024,Poster | Double descent presents a counter-intuitive aspect within the machine learning domain, and researchers have observed its manifestation in various models and tasks. While some theoretical explanations have been proposed for this phenomenon in specific contexts, an accepted theory for its occurring mechanism in deep lear... | https://openreview.net/pdf/01d16ee2c2efbbd0ca37c6d9b32b20eee49faf96.pdf |
Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer | https://openreview.net/forum?id=RthOl4jHw5 | https://openreview.net/forum?id=RthOl4jHw5 | Xingyu Liu,Deepak Pathak,Ding Zhao | ICLR 2024,Poster | We investigate the problem of transferring an expert policy from a source robot to multiple different robots. To solve this problem, we propose a method named *Meta-Evolve* that uses continuous robot evolution to efficiently transfer the policy to each target robot through a set of tree-structured evolutionary robot se... | https://openreview.net/pdf/5ef4fdbe7aea08a39e2674c53de2348273e64350.pdf |
DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation | https://openreview.net/forum?id=h1sFUGlI09 | https://openreview.net/forum?id=h1sFUGlI09 | Bowen Yin,Xuying Zhang,Zhong-Yu Li,Li Liu,Ming-Ming Cheng,Qibin Hou | ICLR 2024,Poster | We present DFormer, a novel RGB-D pretraining framework to learn transferable representations for RGB-D segmentation tasks. DFormer has two new key innovations: 1) Unlike previous works that encode RGB-D information with RGB pretrained backbone, we pretrain the backbone using image-depth pairs from ImageNet-1K, and thu... | https://openreview.net/pdf/04998d857bc9fdde1d3e08fcb47334b0e43a6d15.pdf |
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving | https://openreview.net/forum?id=Ep0TtjVoap | https://openreview.net/forum?id=Ep0TtjVoap | Zhibin Gou,Zhihong Shao,Yeyun Gong,yelong shen,Yujiu Yang,Minlie Huang,Nan Duan,Weizhu Chen | ICLR 2024,Poster | Large language models have made significant progress in various language tasks, yet they still struggle with complex mathematics. In this paper, we propose ToRA a series of Tool-integrated Reasoning Agents designed to solve challenging mathematical problems by seamlessly integrating natural language reasoning with the ... | https://openreview.net/pdf/2b0b45b11d0f61912efb1a932fb494d36f7b88e6.pdf |
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures | https://openreview.net/forum?id=ZYm1Ql6udy | https://openreview.net/forum?id=ZYm1Ql6udy | Ganchao Wei | ICLR 2024,Poster | Modern neural recording techniques allow neuroscientists to obtain spiking activity of multiple neurons from different brain regions over long time periods, which requires new statistical methods to be developed for understanding structure of the large-scale data. In this paper, we develop a bi-clustering method to clu... | https://openreview.net/pdf/9c2a7f237abf74c83846f7f31f5e9f10de0e5c99.pdf |
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data | https://openreview.net/forum?id=XEFWBxi075 | https://openreview.net/forum?id=XEFWBxi075 | Sascha Marton,Stefan Lüdtke,Christian Bartelt,Heiner Stuckenschmidt | ICLR 2024,Poster | Despite the success of deep learning for text and image data, tree-based ensemble models are still state-of-the-art for machine learning with heterogeneous tabular data. However, there is a significant need for tabular-specific gradient-based methods due to their high flexibility. In this paper, we propose $\text{GRAND... | https://openreview.net/pdf/1bbd6ced063094ce68202e826b9d061a03785cea.pdf |
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers | https://openreview.net/forum?id=uJVHygNeSZ | https://openreview.net/forum?id=uJVHygNeSZ | Takeru Miyato,Bernhard Jaeger,Max Welling,Andreas Geiger | ICLR 2024,Poster | As transformers are equivariant to the permutation of input tokens, encoding the positional information of tokens is necessary for many tasks. However, since existing positional encoding schemes have been initially designed for NLP tasks, their suitability for vision tasks, which typically exhibit different structural ... | https://openreview.net/pdf/8b4150f7731750cfa47b7cf419c6929fad3abbc0.pdf |
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models | https://openreview.net/forum?id=ygxTuVz9eU | https://openreview.net/forum?id=ygxTuVz9eU | Zihao Zhu,Mingda Zhang,Shaokui Wei,Bingzhe Wu,Baoyuan Wu | ICLR 2024,Poster | The role of data in building AI systems has recently been emphasized by the emerging concept of data-centric AI. Unfortunately, in the real-world, datasets may contain dirty samples, such as poisoned samples from backdoor attack, noisy labels in crowdsourcing, and even hybrids of them. The presence of such dirty sample... | https://openreview.net/pdf/66009612880b659116956be01719a60fbf3fdbca.pdf |
Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching | https://openreview.net/forum?id=rTBL8OhdhH | https://openreview.net/forum?id=rTBL8OhdhH | Ziyao Guo,Kai Wang,George Cazenavette,HUI LI,Kaipeng Zhang,Yang You | ICLR 2024,Poster | The ultimate goal of Dataset Distillation is to synthesize a small synthetic dataset such that a model trained on this synthetic set will perform equally well as a model trained on the full, real dataset. Until now, no method of Dataset Distillation has reached this completely lossless goal, in part due to the fact tha... | https://openreview.net/pdf/76b4ca911ace4176947d021053d07d288e44f1a2.pdf |
SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning | https://openreview.net/forum?id=vLJcd43U7a | https://openreview.net/forum?id=vLJcd43U7a | Jiacheng Chen,Zeyuan Ma,Hongshu Guo,Yining Ma,Jie Zhang,Yue-Jiao Gong | ICLR 2024,Poster | Recent Meta-learning for Black-Box Optimization (MetaBBO) methods harness neural networks to meta-learn configurations of traditional black-box optimizers. Despite their success, they are inevitably restricted by the limitations of predefined hand-crafted optimizers. In this paper, we present SYMBOL, a novel framework ... | https://openreview.net/pdf/97e4a97ace4b045a200769d9c4b982fa976fb93d.pdf |
SEA: Sparse Linear Attention with Estimated Attention Mask | https://openreview.net/forum?id=JbcwfmYrob | https://openreview.net/forum?id=JbcwfmYrob | Heejun Lee,Jina Kim,Jeffrey Willette,Sung Ju Hwang | ICLR 2024,Poster | The transformer architecture has driven breakthroughs in recent years on tasks
which require modeling pairwise relationships between sequential elements, as
is the case in natural language understanding. However, long seqeuences pose a
problem due to the quadratic complexity of the attention operation. Previous re-
sea... | https://openreview.net/pdf/abc9f142fade538154ad1407071b12115c85b0af.pdf |
Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs | https://openreview.net/forum?id=RZBy8oHTz4 | https://openreview.net/forum?id=RZBy8oHTz4 | Xiong Zhou,Xianming Liu,Feilong Zhang,Gang Wu,Deming Zhai,Junjun Jiang,Xiangyang Ji | ICLR 2024,Poster | Contrastive learning has emerged as a popular paradigm of self-supervised learning that learns representations by encouraging representations of positive pairs to be similar while representations of negative pairs to be far apart. The spectral contrastive loss, in synergy with the notion of positive-pair graphs, offers... | https://openreview.net/pdf/9cb499c6b04df9a78615ec3114dda464d2df3738.pdf |
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data | https://openreview.net/forum?id=yeeVBMDAwy | https://openreview.net/forum?id=yeeVBMDAwy | Xiong Zhou,Xianming Liu,Hao Yu,Jialiang Wang,Zeke Xie,Junjun Jiang,Xiangyang Ji | ICLR 2024,Poster | Graph-based semi-supervised learning, particularly in the context of extremely sparse labeled data, often suffers from degenerate solutions where label functions tend to be nearly constant across unlabeled data. In this paper, we introduce Variance-enlarged Poisson Learning (VPL), a simple yet powerful framework tailor... | https://openreview.net/pdf/df906b36fa0d2fb0102380e2b7e72da2e53d32c8.pdf |
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation | https://openreview.net/forum?id=kx2XZlmgB1 | https://openreview.net/forum?id=kx2XZlmgB1 | Jiyang Zheng,Yu Yao,Bo Han,Dadong Wang,Tongliang Liu | ICLR 2024,Poster | Contrastive learning, while highly effective for a lot of tasks, shows limited improvement in ordinal regression. We find that the limitation comes from the predefined strong data augmentations employed in contrastive learning. Intuitively, for ordinal regression datasets, the discriminative information (ordinal conte... | https://openreview.net/pdf/b2b7b12bdc0cd7d0f495fdc94d0d534fe7af6548.pdf |
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning | https://openreview.net/forum?id=pTHfApDakA | https://openreview.net/forum?id=pTHfApDakA | Ning Miao,Yee Whye Teh,Tom Rainforth | ICLR 2024,Poster | The recent progress in large language models (LLMs), especially the invention of chain-of-thought prompting, has made it possible to automatically answer questions by stepwise reasoning. However, when faced with more complicated problems that require non-linear thinking, even the strongest LLMs make mistakes. To addres... | https://openreview.net/pdf/4abf17ed9d1ca7b68a9c5ee39c9748a16cbab8f7.pdf |
OmniControl: Control Any Joint at Any Time for Human Motion Generation | https://openreview.net/forum?id=gd0lAEtWso | https://openreview.net/forum?id=gd0lAEtWso | Yiming Xie,Varun Jampani,Lei Zhong,Deqing Sun,Huaizu Jiang | ICLR 2024,Poster | We present a novel approach named OmniControl for incorporating flexible spatial control signals into a text-conditioned human motion generation model based on the diffusion process. Unlike previous methods that can only control the pelvis trajectory, OmniControl can incorporate flexible spatial control signals over di... | https://openreview.net/pdf/ccde3adf1de96ef348db1adc995af579e407bada.pdf |
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators | https://openreview.net/forum?id=QJGj07PD9C | https://openreview.net/forum?id=QJGj07PD9C | Renbo Tu,Colin White,Jean Kossaifi,Boris Bonev,Gennady Pekhimenko,Kamyar Azizzadenesheli,Anima Anandkumar | ICLR 2024,Poster | Neural operators, such as Fourier Neural Operators (FNO), form a principled approach for learning solution operators for partial differential equations (PDE) and other mappings between function spaces. However, many real-world problems require high-resolution training data, and the training time and limited GPU memory ... | https://openreview.net/pdf/6c0041c80aa708b16a4dd909b572745445905c4c.pdf |
Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields | https://openreview.net/forum?id=w7BwaDHppp | https://openreview.net/forum?id=w7BwaDHppp | Junoh Lee,Hyunjun Jung,Jin-Hwi Park,Inhwan Bae,Hae-Gon Jeon | ICLR 2024,Poster | Estimating neural radiance fields (NeRFs) is able to generate novel views of a scene from known imagery. Recent approaches have afforded dramatic progress on small bounded regions of the scene. For an unbounded scene where cameras point in any direction and contents exist at any distance, certain mapping functions are ... | https://openreview.net/pdf/9a380db5c8eddb8e8366c87500c05613bc30bcc7.pdf |
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes | https://openreview.net/forum?id=Gf15GsnfTy | https://openreview.net/forum?id=Gf15GsnfTy | David Ireland,Giovanni Montana | ICLR 2024,Poster | Discrete-action reinforcement learning algorithms often falter in tasks with high-dimensional discrete action spaces due to the vast number of possible actions. A recent advancement leverages value-decomposition, a concept from multi-agent reinforcement learning, to tackle this challenge. This study delves deep into th... | https://openreview.net/pdf/7c65f83a959b080c4e7067cfb42e34fe41ed7631.pdf |
Path Choice Matters for Clear Attributions in Path Methods | https://openreview.net/forum?id=gzYgsZgwXa | https://openreview.net/forum?id=gzYgsZgwXa | Borui Zhang,Wenzhao Zheng,Jie Zhou,Jiwen Lu | ICLR 2024,Poster | Rigorousness and clarity are both essential for interpretations of DNNs to engender human trust. Path methods are commonly employed to generate rigorous attributions that satisfy three axioms. However, the meaning of attributions remains ambiguous due to distinct path choices. To address the ambiguity, we introduce Con... | https://openreview.net/pdf/fdfec76299aea6f4172a06958754d19d20b2be55.pdf |
Exploring Target Representations for Masked Autoencoders | https://openreview.net/forum?id=xmQMz9OPF5 | https://openreview.net/forum?id=xmQMz9OPF5 | xingbin liu,Jinghao Zhou,Tao Kong,Xianming Lin,Rongrong Ji | ICLR 2024,Poster | Masked autoencoders have become popular training paradigms for self-supervised visual representation learning. These models randomly mask a portion of the input and reconstruct the masked portion according to assigned target representations. In this paper, we show that a careful choice of the target representation is u... | https://openreview.net/pdf/d05fab1c9b21d690b4a92e177803416cdf36d678.pdf |
Koopman-based generalization bound: New aspect for full-rank weights | https://openreview.net/forum?id=JN7TcCm9LF | https://openreview.net/forum?id=JN7TcCm9LF | Yuka Hashimoto,Sho Sonoda,Isao Ishikawa,Atsushi Nitanda,Taiji Suzuki | ICLR 2024,Poster | We propose a new bound for generalization of neural networks using Koopman operators. Whereas most of existing works focus on low-rank weight matrices, we focus on full-rank weight matrices. Our bound is tighter than existing norm-based bounds when the condition numbers of weight matrices are small. Especially, it is c... | https://openreview.net/pdf/39b09431cd59c08f98c5e21c1cc1d7783a995df4.pdf |
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis | https://openreview.net/forum?id=aA33A70IO6 | https://openreview.net/forum?id=aA33A70IO6 | Kai Chen,Chunwei Wang,Kuo Yang,Jianhua Han,Lanqing HONG,Fei Mi,Hang Xu,Zhengying Liu,Wenyong Huang,Zhenguo Li,Dit-Yan Yeung,Lifeng Shang | ICLR 2024,Poster | The rapid development of large language models (LLMs) has not only provided numerous opportunities but also presented significant challenges. This becomes particularly evident when LLMs inadvertently generate harmful or toxic content, either unintentionally or because of intentional inducement. Existing alignment metho... | https://openreview.net/pdf/d3ae49610289200e85da374558dbfbd71bad4ae5.pdf |
MagicDrive: Street View Generation with Diverse 3D Geometry Control | https://openreview.net/forum?id=sBQwvucduK | https://openreview.net/forum?id=sBQwvucduK | Ruiyuan Gao,Kai Chen,Enze Xie,Lanqing HONG,Zhenguo Li,Dit-Yan Yeung,Qiang Xu | ICLR 2024,Poster | Recent advancements in diffusion models have significantly enhanced the data synthesis with 2D control. Yet, precise 3D control in street view generation, crucial for 3D perception tasks, remains elusive. Specifically, utilizing Bird's-Eye View (BEV) as the primary condition often leads to challenges in geometry contro... | https://openreview.net/pdf/24ee27e06af8a9a4d217bf99e7d46340c5b078b0.pdf |
MogaNet: Multi-order Gated Aggregation Network | https://openreview.net/forum?id=XhYWgjqCrV | https://openreview.net/forum?id=XhYWgjqCrV | Siyuan Li,Zedong Wang,Zicheng Liu,Cheng Tan,Haitao Lin,Di Wu,Zhiyuan Chen,Jiangbin Zheng,Stan Z. Li | ICLR 2024,Poster | By contextualizing the kernel as global as possible, Modern ConvNets have shown great potential in computer vision tasks. However, recent progress on \textit{multi-order game-theoretic interaction} within deep neural networks (DNNs) reveals the representation bottleneck of modern ConvNets, where the expressive interact... | https://openreview.net/pdf/c97ca9c77b004d29ce9d4a0ee49d8c4af7c66111.pdf |
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation | https://openreview.net/forum?id=xBfQZWeDRH | https://openreview.net/forum?id=xBfQZWeDRH | Kai Chen,Enze Xie,Zhe Chen,Yibo Wang,Lanqing HONG,Zhenguo Li,Dit-Yan Yeung | ICLR 2024,Poster | Diffusion models have attracted significant attention due to the remarkable ability to create content and generate data for tasks like image classification. However, the usage of diffusion models to generate the high-quality object detection data remains an underexplored area, where not only image-level perceptual qual... | https://openreview.net/pdf/4120084299533337d90cfa998fd0b8592f8587ac.pdf |
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation | https://openreview.net/forum?id=xyxU99Nutg | https://openreview.net/forum?id=xyxU99Nutg | Devavrat Tomar,Guillaume Vray,Jean-Philippe Thiran,Behzad Bozorgtabar | ICLR 2024,Poster | Recent test-time adaptation methods heavily rely on nuanced adjustments of batch normalization (BN) parameters. However, one critical assumption often goes overlooked: that of independently and identically distributed (i.i.d.) test batches with respect to unknown labels. This oversight leads to skewed BN statistics an... | https://openreview.net/pdf/60cb9a745b90bacd6f6b78a18bb6e64215a62c5d.pdf |
Constraint-Free Structure Learning with Smooth Acyclic Orientations | https://openreview.net/forum?id=KWO8LSUC5W | https://openreview.net/forum?id=KWO8LSUC5W | Riccardo Massidda,Francesco Landolfi,Martina Cinquini,Davide Bacciu | ICLR 2024,Poster | The structure learning problem consists of fitting data generated by a Directed Acyclic Graph (DAG) to correctly reconstruct its arcs. In this context, differentiable approaches constrain or regularize an optimization problem with a continuous relaxation of the acyclicity property. The computational cost of evaluating ... | https://openreview.net/pdf/59eb1510b8ba77c7b7be42e8ab1b96dd793c2bea.pdf |
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution | https://openreview.net/forum?id=b66P1u0k15 | https://openreview.net/forum?id=b66P1u0k15 | Zhipeng Zhou,Liu Liu,Peilin Zhao,Wei Gong | ICLR 2024,Poster | Deep long-tailed recognition (DTLR) has attracted much attention due to its close touch with realistic scenarios. Recent advances have focused on re-balancing across various aspects, e.g., sampling strategy, loss re-weighting, logit adjustment, and input/parameter perturbation, to name a few. However, few studies have ... | https://openreview.net/pdf/010f844268393128404f69bc7fb505b83bea6aa6.pdf |
MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection | https://openreview.net/forum?id=Q1vkAhdI6j | https://openreview.net/forum?id=Q1vkAhdI6j | Yuxue Yang,Lue Fan,Zhaoxiang Zhang | ICLR 2024,Poster | Label-efficient LiDAR-based 3D object detection is currently dominated by weakly/semi-supervised methods. Instead of exclusively following one of them, we propose MixSup, a more practical paradigm simultaneously utilizing massive cheap coarse labels and a limited number of accurate labels for Mixed-grained Supervision.... | https://openreview.net/pdf/8ff478f64c38c91591fa7296da064a4fc05b28a9.pdf |
Boosting Vanilla Lightweight Vision Transformers via Re-parameterization | https://openreview.net/forum?id=3rmpixOjPS | https://openreview.net/forum?id=3rmpixOjPS | Zhentao Tan,Xiaodan Li,Yue Wu,Qi Chu,Le Lu,Nenghai Yu,Jieping Ye | ICLR 2024,Poster | Large-scale Vision Transformers have achieved promising performance on downstream tasks through feature pre-training. However, the performance of vanilla lightweight Vision Transformers (ViTs) is still far from satisfactory compared to that of recent lightweight CNNs or hybrid networks. In this paper, we aim to unlock ... | https://openreview.net/pdf/f669c82db24753f05848f03ca1491e10580fb946.pdf |
Robust Angular Synchronization via Directed Graph Neural Networks | https://openreview.net/forum?id=5sjxMwWmk8 | https://openreview.net/forum?id=5sjxMwWmk8 | Yixuan He,Gesine Reinert,David Wipf,Mihai Cucuringu | ICLR 2024,Poster | The angular synchronization problem aims to accurately estimate (up to a constant additive phase) a set of unknown angles $\theta_1, \dots, \theta_n\in[0, 2\pi)$ from $m$ noisy measurements of their offsets $\theta_i-\theta_j$ mod $2\pi.$ Applications include, for example, sensor network localization, phase retrieval, ... | https://openreview.net/pdf/492b774f3c98c936bb4b4dd64aca6ce4f392fdbc.pdf |
Multi-Scale Representations by Varying Window Attention for Semantic Segmentation | https://openreview.net/forum?id=lAhWGOkpSR | https://openreview.net/forum?id=lAhWGOkpSR | Haotian Yan,Ming Wu,Chuang Zhang | ICLR 2024,Poster | Multi-scale learning is central to semantic segmentation. We visualize the effective receptive field (ERF) of canonical multi-scale representations and point out two risks learning them: \textit{scale inadequacy} and \textit{field inactivation}. A novel multi-scale learner, \textbf{varying window attention} (VWA), is p... | https://openreview.net/pdf/5759da5cdff163afbc7e96513ae3bb41d52ce451.pdf |
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity | https://openreview.net/forum?id=hbHwZYqk9T | https://openreview.net/forum?id=hbHwZYqk9T | Kai Yi,Nidham Gazagnadou,Peter Richtárik,Lingjuan Lyu | ICLR 2024,Poster | The interest in federated learning has surged in recent research due to its unique ability to train a global model using privacy-secured information held locally on each client. This paper pays particular attention to the issue of client-side model heterogeneity, a pervasive challenge in the practical implementation of... | https://openreview.net/pdf/f764a286e9019ed1fa4d66fad2d0df88386d6454.pdf |
Compressed Context Memory for Online Language Model Interaction | https://openreview.net/forum?id=64kSvC4iPg | https://openreview.net/forum?id=64kSvC4iPg | Jang-Hyun Kim,Junyoung Yeom,Sangdoo Yun,Hyun Oh Song | ICLR 2024,Poster | This paper presents a context key/value compression method for Transformer language models in online scenarios, where the context continually expands. As the context lengthens, the attention process demands increasing memory and computations, which in turn reduces the throughput of the language model. To address this c... | https://openreview.net/pdf/b1ec67610e0db6c622b1745257004d5f79b63f38.pdf |
TUVF: Learning Generalizable Texture UV Radiance Fields | https://openreview.net/forum?id=dN4vpVTvWX | https://openreview.net/forum?id=dN4vpVTvWX | An-Chieh Cheng,Xueting Li,Sifei Liu,Xiaolong Wang | ICLR 2024,Poster | Textures are a vital aspect of creating visually appealing and realistic 3D models. In this paper, we study the problem of generating high-fidelity texture given shapes of 3D assets, which has been relatively less explored compared with generic 3D shape modeling. Our goal is to facilitate a controllable texture generat... | https://openreview.net/pdf/e3ed9ed07f700f15cfa92ddec1c528a47e174a1a.pdf |
Neural Processing of Tri-Plane Hybrid Neural Fields | https://openreview.net/forum?id=zRkM6UcA22 | https://openreview.net/forum?id=zRkM6UcA22 | Adriano Cardace,Pierluigi Zama Ramirez,Francesco Ballerini,Allan Zhou,Samuele Salti,Luigi di Stefano | ICLR 2024,Poster | Driven by the appealing properties of neural fields for storing and communicating 3D data, the problem of directly processing them to address tasks such as classification and part segmentation has emerged and has been investigated in recent works.
Early approaches employ neural fields parameterized by shared networks ... | https://openreview.net/pdf/93609429dd87387881b65722dd6a3c89e5c92e2e.pdf |
Large-Vocabulary 3D Diffusion Model with Transformer | https://openreview.net/forum?id=q57JLSE2j5 | https://openreview.net/forum?id=q57JLSE2j5 | Ziang Cao,Fangzhou Hong,Tong Wu,Liang Pan,Ziwei Liu | ICLR 2024,Poster | Creating diverse and high-quality 3D assets with an automatic generative model is highly desirable. Despite extensive efforts on 3D generation, most existing works focus on the generation of a single category or a few categories. In this paper, we introduce a diffusion-based feed-forward framework for synthesizing mass... | https://openreview.net/pdf/bc3224f45f98c7433120bdba86c0cec3c95a10be.pdf |
SAS: Structured Activation Sparsification | https://openreview.net/forum?id=vZfi5to2Xl | https://openreview.net/forum?id=vZfi5to2Xl | Yusuke Sekikawa,Shingo Yashima | ICLR 2024,Poster | Wide networks usually yield better accuracy than their narrower counterpart at the expense of the massive $\texttt{mult}$ cost.
To break this tradeoff, we advocate a novel concept of $\textit{Structured Activation Sparsification}$, dubbed SAS, which boosts accuracy without increasing computation by utilizing the projec... | https://openreview.net/pdf/46b950fc8d399323be1b9f3146b99dfc92260653.pdf |
A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model | https://openreview.net/forum?id=g52tgL8jy6 | https://openreview.net/forum?id=g52tgL8jy6 | Zecheng Hao,Xinyu Shi,Zihan Huang,Tong Bu,Zhaofei Yu,Tiejun Huang | ICLR 2024,Poster | Spiking Neural Networks (SNNs) have garnered considerable attention due to their energy efficiency and unique biological characteristics. However, the widely adopted Leaky Integrate-and-Fire (LIF) model, as the mainstream neuron model in current SNN research, has been revealed to exhibit significant deficiencies in dee... | https://openreview.net/pdf/d72a759c89415e0f33d04dd3245a137044d9fcfe.pdf |
Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis | https://openreview.net/forum?id=mvMI3N4AvD | https://openreview.net/forum?id=mvMI3N4AvD | Ziyue Jiang,Jinglin Liu,Yi Ren,Jinzheng He,Zhenhui Ye,Shengpeng Ji,Qian Yang,Chen Zhang,Pengfei Wei,Chunfeng Wang,Xiang Yin,Zejun MA,Zhou Zhao | ICLR 2024,Poster | Zero-shot text-to-speech (TTS) aims to synthesize voices with unseen speech prompts, which significantly reduces the data and computation requirements for voice cloning by skipping the fine-tuning process. However, the prompting mechanisms of zero-shot TTS still face challenges in the following aspects: 1) previous wor... | https://openreview.net/pdf/9cd6af4b3063c11b7dba3aa572d8ab74e7274f8e.pdf |
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors | https://openreview.net/forum?id=FOSBQuXgAq | https://openreview.net/forum?id=FOSBQuXgAq | Olivier Laurent,Emanuel Aldea,Gianni Franchi | ICLR 2024,Poster | The distribution of modern deep neural networks (DNNs) weights -- crucial for uncertainty quantification and robustness -- is an eminently complex object due to its extremely high dimensionality. This paper presents one of the first large-scale explorations of the posterior distribution of deep Bayesian Neural Networks... | https://openreview.net/pdf/68b6225f7dd97251741d9909405fe064b3f02a65.pdf |
Threaten Spiking Neural Networks through Combining Rate and Temporal Information | https://openreview.net/forum?id=xv8iGxENyI | https://openreview.net/forum?id=xv8iGxENyI | Zecheng Hao,Tong Bu,Xinyu Shi,Zihan Huang,Zhaofei Yu,Tiejun Huang | ICLR 2024,Poster | Spiking Neural Networks (SNNs) have received widespread attention in academic communities due to their superior spatio-temporal processing capabilities and energy-efficient characteristics. With further in-depth application in various fields, the vulnerability of SNNs under adversarial attack has become a focus of conc... | https://openreview.net/pdf/6f08ceb0b9c1fe0346b48c7b0a316ede64f412f3.pdf |
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models | https://openreview.net/forum?id=FIplmUWdm3 | https://openreview.net/forum?id=FIplmUWdm3 | Jing Liu,Ruihao Gong,Xiuying Wei,Zhiwei Dong,Jianfei Cai,Bohan Zhuang | ICLR 2024,Poster | Large Language Models (LLMs) have demonstrated unparalleled efficacy in natural language processing. However, their high computational demands and memory overheads hinder their broad deployment. To address this, two quantization strategies emerge, including Quantization-Aware Training (QAT) and Post-Training Quantizati... | https://openreview.net/pdf/8b8aeb5a8b38f435b1b5d6ed2806ae8e391276b1.pdf |
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation | https://openreview.net/forum?id=U6hEOZlDf5 | https://openreview.net/forum?id=U6hEOZlDf5 | Chen Zhao,Tong Zhang,Mathieu Salzmann | ICLR 2024,Poster | Prior methods that tackle the problem of generalizable object pose estimation highly rely on having dense views of the unseen object. By contrast, we address the scenario where only a single reference view of the object is available. Our goal then is to estimate the relative object pose between this reference view and ... | https://openreview.net/pdf/c7f0109d51e7535da0efad4d433011e24c46a0f5.pdf |
Language Model Self-improvement by Reinforcement Learning Contemplation | https://openreview.net/forum?id=38E4yUbrgr | https://openreview.net/forum?id=38E4yUbrgr | Jing-Cheng Pang,Pengyuan Wang,Kaiyuan Li,Xiong-Hui Chen,Jiacheng Xu,Zongzhang Zhang,Yang Yu | ICLR 2024,Poster | Language model self-improvement (LMSI) techniques have recently gained significant attention as they improve language models without requiring external supervision. A common approach is reinforcement learning from AI feedback (RLAIF), which trains a reward model based on AI preference data and employs a reinforcement l... | https://openreview.net/pdf/fbf1dbb2ce060d40c6445d59f06ab77e43d99c31.pdf |
Divide and not forget: Ensemble of selectively trained experts in Continual Learning | https://openreview.net/forum?id=sSyytcewxe | https://openreview.net/forum?id=sSyytcewxe | Grzegorz Rypeść,Sebastian Cygert,Valeriya Khan,Tomasz Trzcinski,Bartosz Michał Zieliński,Bartłomiej Twardowski | ICLR 2024,Poster | Class-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using w... | https://openreview.net/pdf/ca11ed77ce19ec235f48c2e3055087722f6cff3c.pdf |
Towards Offline Opponent Modeling with In-context Learning | https://openreview.net/forum?id=2SwHngthig | https://openreview.net/forum?id=2SwHngthig | Yuheng Jing,Kai Li,Bingyun Liu,Yifan Zang,Haobo Fu,QIANG FU,Junliang Xing,Jian Cheng | ICLR 2024,Poster | Opponent modeling aims at learning the opponent's behaviors, goals, or beliefs to reduce the uncertainty of the competitive environment and assist decision-making. Existing work has mostly focused on learning opponent models online, which is impractical and inefficient in practical scenarios. To this end, we formalize ... | https://openreview.net/pdf/ebdbd616b536556e85afb869974a43d60b721e11.pdf |
Early Stopping Against Label Noise Without Validation Data | https://openreview.net/forum?id=CMzF2aOfqp | https://openreview.net/forum?id=CMzF2aOfqp | Suqin Yuan,Lei Feng,Tongliang Liu | ICLR 2024,Poster | Early stopping methods in deep learning face the challenge of balancing the volume of training and validation data, especially in the presence of label noise. Concretely, sparing more data for validation from training data would limit the performance of the learned model, yet insufficient validation data could result i... | https://openreview.net/pdf/b11f54e4a5242e8130e556b3848fdcd44bae997f.pdf |
Recursive Generalization Transformer for Image Super-Resolution | https://openreview.net/forum?id=owziuM1nsR | https://openreview.net/forum?id=owziuM1nsR | Zheng Chen,Yulun Zhang,Jinjin Gu,Linghe Kong,Xiaokang Yang | ICLR 2024,Poster | Transformer architectures have exhibited remarkable performance in image super-resolution (SR). Since the quadratic computational complexity of the self-attention (SA) in Transformer, existing methods tend to adopt SA in a local region to reduce overheads. However, the local design restricts the global context exploita... | https://openreview.net/pdf/cedcaa8b38ce2730b25e4b03d432a016574ef3bd.pdf |
Rethinking Model Ensemble in Transfer-based Adversarial Attacks | https://openreview.net/forum?id=AcJrSoArlh | https://openreview.net/forum?id=AcJrSoArlh | Huanran Chen,Yichi Zhang,Yinpeng Dong,Xiao Yang,Hang Su,Jun Zhu | ICLR 2024,Poster | It is widely recognized that deep learning models lack robustness to adversarial examples. An intriguing property of adversarial examples is that they can transfer across different models, which enables black-box attacks without any knowledge of the victim model. An effective strategy to improve the transferability is ... | https://openreview.net/pdf/20c70b93e487bdad50b8ad236e2f42ce1e19ec4a.pdf |
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited | https://openreview.net/forum?id=hOxgrGM63n | https://openreview.net/forum?id=hOxgrGM63n | Lu Yu,Avetik Karagulyan,Arnak S. Dalalyan | ICLR 2024,Poster | We revisit the problem of sampling from a target distribution that has a smooth strongly log-concave density everywhere in $\mathbb{R}^p$. In this context, if no additional density information is available, the randomized midpoint discretization for the kinetic Langevin diffusion is known to be the most scalable method... | https://openreview.net/pdf/8be6e385e53c2c9a2af47b0d45a4e85bee6910bd.pdf |
MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images | https://openreview.net/forum?id=AHgc5SMdtd | https://openreview.net/forum?id=AHgc5SMdtd | Xurui Li,Ziming Huang,Feng Xue,Yu Zhou | ICLR 2024,Poster | This paper studies zero-shot anomaly classification (AC) and segmentation (AS) in industrial vision.
We reveal that the abundant normal and abnormal cues implicit in unlabeled test images can be exploited for anomaly determination, which is ignored by prior methods.
Our key observation is that for the industrial produc... | https://openreview.net/pdf/dd0c9086175785e7480d6c5302f62df0f492be98.pdf |
To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination | https://openreview.net/forum?id=m2NVG4Htxs | https://openreview.net/forum?id=m2NVG4Htxs | Manley Roberts,Himanshu Thakur,Christine Herlihy,Colin White,Samuel Dooley | ICLR 2024,Poster | Recent claims about the impressive abilities of large language models (LLMs) are often supported by evaluating publicly available benchmarks.
Since LLMs train on wide swaths of the internet, this practice raises concerns of data contamination, i.e., evaluating on examples that are explicitly or implicitly included in ... | https://openreview.net/pdf/1e44de0b013ebf5d819d5fe1e140585af153cda3.pdf |
I-PHYRE: Interactive Physical Reasoning | https://openreview.net/forum?id=1bbPQShCT2 | https://openreview.net/forum?id=1bbPQShCT2 | Shiqian Li,Kewen Wu,Chi Zhang,Yixin Zhu | ICLR 2024,Poster | Current evaluation protocols predominantly assess physical reasoning in stationary scenes, creating a gap in evaluating agents' abilities to interact with dynamic events. While contemporary methods allow agents to modify initial scene configurations and observe consequences, they lack the capability to interact with ev... | https://openreview.net/pdf/fad4695ed5caf629961f820cfffbd439e4662aa5.pdf |
Exposing Text-Image Inconsistency Using Diffusion Models | https://openreview.net/forum?id=Ny150AblPu | https://openreview.net/forum?id=Ny150AblPu | Mingzhen Huang,Shan Jia,Zhou Zhou,Yan Ju,Jialing Cai,Siwei Lyu | ICLR 2024,Poster | In the battle against widespread online misinformation, a growing problem is text-image inconsistency, where images are misleadingly paired with texts with different intent or meaning. Existing classification-based methods for text-image inconsistency can identify contextual inconsistencies but fail to provide explaina... | https://openreview.net/pdf/5ef14ecda408daf8c2e2a2063612332fe824cf04.pdf |
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