paper_id stringlengths 10 10 | items listlengths 4 82 | gt float64 1 9.5 |
|---|---|---|
NlY3XppPt3 | [
"strength: The underlying goal of this work is to create test cases that would push the capabilities of large language models to the limit. This is a valid and important endeavor.",
"strength: This paper correctly identifies generalisation of models to unseen circumstances as a critically important facet of progr... | 2 |
BltaWJZMeR | [
"strength: This work presents a new benchmark dataset for evaluating LLMs on data science tasks, which is a meaningful contribution to the community.",
"strength: The benchmark covers representative task types in data science, from data processing to data mining and report generation.",
"strength: The evaluatio... | 3.2 |
zSHoaTNlmA | [
"strength: The proposed method improves the segmentation results based on the transformer architecture, which is lightweight.",
"strength: Innovative Approach: The paper presents a novel method, SERNet-Former, which combines Efficient-ResNet with attention mechanisms, demonstrating a promising advancement in segm... | 3.5 |
ybiwT2yP1c | [
"strength: The benchmark is a nice real-world application on measuring generalization in the field of bioacoustics, which could be interested for practitioners.",
"strength: Evaluation protocol is simple to follow/apply, i.e. models are used as feature extractors and the task is simple retrieval.",
"strength: A... | 5 |
ZyMXxpBfct | [
"strength: Tackles important problem of understanding forgetting in NNs.",
"strength: Investigating the catastrophic forgetting issue is very relevant to the community.",
"strength: The authors thoroughly look at the problem of catastrophic forgetting and in general of neural network training in a thorough fash... | 1.5 |
I86z54CL2y | [
"strength: The problem is of interest to the research community.",
"strength: The paper is easy to follow.",
"strength: The paper tackles an interesting and very challenging task of single-view 3D object reconstruction.",
"strength: The experimental evaluation shows strong performance with advantages over bas... | 3.4 |
kXHEBK9uAY | [
"strength: Using a hierarchical structure makes sense in long-horizon planning.",
"strength: In replanning, a hierarchical structure is more efficient since it only needs to use low-level to",
"strength: Show the relationship between kernel size and generalization.",
"strength: Discretizing planning into sub-... | 5.75 |
H380m98pLE | [
"strength: The problem is well-motivated, timely, and sufficiently well-positioned in the literature",
"strength: The proposed method appears straightforward to apply and seems to be effective in the proposed experiments",
"strength: The paper is clearly written and organized",
"strength: The paper tackles an... | 2.5 |
tuzTN0eIO5 | [
"strength: I think splitting the backward pass into B (activation gradient computation) and W (weight gradient computation) as a way of improving scheduling flexibility is a nice touch of creativity.",
"strength: The paper includes ample analytical details that foster intuition and understanding of the relevant m... | 7 |
bKswCSYkKq | [
"strength: The paper is well-written, presenting complex ideas clearly and understandably.",
"strength: It introduces a novel method for identifying \"activated\" neurons, contributing a fresh perspective on neuron-level balancing between stability and plasticity in deep reinforcement learning. This approach, whi... | 3 |
zGb4WgCW5i | [
"strength: Simple method which is very easy to use",
"strength: Good insights from eigenspectrum variance",
"strength: Constantly improve the decoding methods of InstructBLIP, MiniGPT-4, LLaVA-1.5, and Shikra.",
"strength: This paper provides a solid theoretical framework by analyzing the relationship between... | 7 |
lmYGRGyL4i | [
"strength: It is interesting to bridge one-shot and sequential graph generation methods with a unified framework.",
"strength: Authors provide the analysis of the sample quality-time trade-off across many real-world datasets.",
"strength: The paper is well-written and easy to understand.",
"strength: Explorin... | 4.8 |
KjxZ4BdUdN | [
"strength: This paper considers breaking down the pre-inference to post-inference life cycle into different modules, and comes up with techniques to improve safety and reliability for each step. The various modules are also flexible and adaptable. The paper provides an open-source attempt to replicate the safety/ r... | 3 |
yBLBls6ryd | [
"strength: The authors introduce a unifying framework for a class of preconditioned gradient agorithms as special cases of fractional natural gradient descent, and gives a general framework to implement it more efficiently in a spectral parameterization that is motivated by a Riemannian optimization algorithm in a ... | 4.857143 |
5Ca9sSzuDp | [
"strength: This paper presents important timely study to understand the inner working of image backbones of the large scale vision-language models like CLIP which has become a very popular paradigm. This will help to improve the next generation of such models in terms of architecture and training.",
"strength: Th... | 8 |
rZzcaduYU1 | [
"strength: The integration of score-based generative models within the NP framework is a novel approach.",
"strength: The theoretical foundation is robust- the proofs and methodology enhance trust in the results.",
"strength: The VLB objective is also a novel extension of likelihood re-weighting.",
"strength:... | 3 |
GlAeL0I8LX | [
"strength: The paper studies global an important question in explainable machine learning, providing global interpretation through user defined features.",
"strength: The paper motivation is well justified, well-written and easy to understand.",
"strength: The results show that QPM achieves superior performanc... | 6.666667 |
xXTkbTBmqq | [
"strength: The writing in this paper is clear and easy to follow.",
"strength: The paper advances MoE research by providing a fully open-sourced, state-of-the-art MoE architecture, which is beneficial for the research community.",
"strength: The paper presents a thorough analysis of key design choices in MoE, o... | 8.666667 |
97rOQDPmk2 | [
"strength: The paper offers a comprehensive four-stage analysis of transformer training dynamics, which is a promising contribution to understanding the behavior of transformers.",
"strength: The demonstration of fast convergence but poor generalization with SignGD on noisy data is important. These findings are b... | 7.333333 |
pz0EK4g6AN | [
"strength: The paper introduces QCircuitNet, and it provides a comprehensive structure, including benchmarks, automatic validation, and compatibility with various algorithms. Additionally, it offers a unique framework for large language models by formulating quantum algorithms as programming tasks.",
"strength: Q... | 4.75 |
Rd1pjx84rk | [
"strength: The spectral analysis along with the solutions are well-motivated and interesting to the community;",
"strength: The paper is well-written and easy to follow;",
"strength: This paper identifies that cycle-related information plays a pivotal role in reducing spectral differences between small and larg... | 5 |
10kBEqYKKN | [
"strength: The idea of studying the effects of prompts through the geometry of latent representations is interesting.",
"strength: The paper tries to address the intriguing question of how prompt representations relate to model performance, with a specific focus on how prompt formulation impacts performance robus... | 3 |
kKRbAY4CXv | [
"strength: Innovative Approach: The paper introduces a novel approach, NEKM, which combines operator splitting, boundary integral techniques, and Deep Neural Networks (DNNs) to address the solution of time-dependent semi-linear Partial Differential Equations (PDEs). This innovation offers a fresh perspective on tac... | 4.25 |
k3LAIS5wTY | [
"strength: The authors address an important open issue in the evaluation of dynamic link prediction",
"strength: The authors combine the approach of counterfactual analysis from causal inference and apply it to the evaluation of temporal graph learning. To the best of my knowledge, this is a novel combination (ev... | 4.25 |
Idygh9MX0N | [
"strength: The idea of using multi-agent systems to solve causal discovery problem is interesting.",
"strength: Comprehensive Multi-Agent Approach: The paper introduces a well-structured framework that incorporates debate, planning, and coding agents to address causal inference, allowing MAC to explore causal dis... | 3.4 |
mWxcEm7jIv | [
"strength: The proposed method is simple but effective.",
"strength: Incorporating denoised examples into the classifiers is a reasonable approach to improve performance.",
"strength: Additionally, it is worth noting that they address partial supervision settings, although they did not provide the result on ima... | 4.75 |
bOoHGBwFoo | [
"strength: The paper is well-structured and clearly written, making it easy to follow and understand.",
"strength: The approach of using an LLM and a diffusion model to generate missing data for unseen classes is novel.",
"strength: By generating images and descriptions, the method reframes the zero-shot learni... | 4.5 |
zl0HLZOJC9 | [
"strength: The paper addresses a research question relevant to real-world applications by providing a solution for settings where expert annotations are incomplete.",
"strength: The results show that reducing the workload of highly accurate (and typically overloaded) human experts only slightly decreases overall ... | 8 |
FJjHQS2DyE | [
"strength: This paper proposed conditional adversarial support alignment (CASA) to minimize the conditional symmetric support divergence between the source’s and target domain’s feature representation distributions.",
"strength: Generally, the paper is well-written and easy to follow.",
"strength: They evaluate... | 5.666667 |
C9BA0T3xhq | [
"strength: The problem being worked on is well-motivated and important.",
"strength: There are a lot of experiments with potentially significant results.",
"strength: The paper is well structured. The proposed idea is simple and easy to implement.",
"strength: Empirical results are provided on various robotic... | 2 |
X2x2DuGIbx | [
"strength: The paper is very well presented. As someone who is not very familiar with RL poisoning, or certified defenses to poisoning, I think the exposition and organization in the paper was great. The flow was logical and the writing, definitions, and lemmas/theorems were all clear.",
"strength: The experiment... | 6.75 |
1mjsP8RYAw | [
"strength: The author's idea of leveraging a knowledge graph to produce positive and negative examples of unlabeled claims to train a scoring model is creative.",
"strength: The paper is very well-structured, and easy to follow.",
"strength: The experiments presented promising results on FEVER (~8% improvement ... | 6 |
ccxD4mtkTU | [
"strength: The paper does a good job at describing the problem statement and their contributions. It's a good survey on the related techniques within this space.",
"strength: The misinformation taxonomy and the generation strategies of hallucination, Arbitrary Misinformation and Controllable Misinformation genera... | 4.75 |
tfp4FxWCC8 | [
"strength: I could not find any previous work integrating TDA and diffusion models in this manner, so props for creativity. The results uniformly seem improved.",
"strength: The derive theoretical stability guarantees of the proposed topological features of generated data.",
"strength: Extensive empirical evalu... | 6.5 |
BxPqibGUPR | [
"strength: The idea is interesting, i.e., synthesizing vector space via prompting LLMs to generate entities and relations of entities, especially those cross-domain relations.",
"strength: Timely study on how well can LLMs generate entities and relations of entities.",
"strength: The paper is well-written and e... | 3 |
CLE09ESvul | [
"strength: The topic of biologically inspired neural networks has attracted great attention in the recent years. Proposing alternative solutions to the long-dominating backpropagation method is also interesting and profoundly influential. I encourage the authors to work along these lines.",
"strength: Overall thi... | 7.5 |
wHsAi8kINK | [
"strength: The design idea of dividing the client neural network into three parts and training them using a two-stage strategy has some practical application value.",
"strength: Propose a new framework to enhance both global and local FL performance.",
"strength: Experiments indicate that the proposed Fed3+2p m... | 3.666667 |
Zap3nZhRIQ | [
"strength: The paper is mostly well-written, both in terms of language and, flow and literature review. It is also sound. The paper may motivate research towards the training of non-differentiable neural networks.",
"strength: This paper studies non-differentiability in deep learning, which is an important issue.... | 3 |
uswS6tUCN2 | [
"strength: This paper performs extensive experiments to thoroughly demonstrate the capability of the proposed method.",
"strength: The proposed method improves inference speed and reduces the model size of implicit 3D representations.",
"strength: The proposed method is well-analyzed through kernel estimation m... | 5.333333 |
epFk8e470p | [
"strength: This paper propose novel ideas of incorporating inductive bias from neuroscience in building artificial neural networks and shows that it does improve the performance of action recognition when compared with a baseline network.",
"strength: The paper is well-written and very clear.",
"strength: The h... | 1.666667 |
HW8xnOUcBx | [
"strength: Fitting to 3D point clouds, or sometimes called registrations, has long been studied in 3D Vision/Graphics community. Besides the observed 3D points, recent state-of-the-art methods often leverage 2D detectors, e.g., human joint detection as a complementary supervision signal. This is how existing benchm... | 4.5 |
070DFUdNh7 | [
"strength: The paper proposed an interesting angle for graph pretraining, which takes advantage of the great performance of the breakthrough of LLM (transformer) into graph learning.",
"strength: The idea of Eulerian path is also interesting.",
"strength: The paper has investigated various graph tasks, includin... | 4.5 |
gI0kPklUKS | [
"strength: This work distinguishes itself from existing approaches to interpretable neural networks by using a unique characteristic of bilinear MLPs. While previous works have utilized bilinear MLP networks, this paper uniquely demonstrates how to exploit their inherent differences from other MLPs to achieve inter... | 7.5 |
SLUr06QUuw | [
"strength: This submission is well written and easy to follow.",
"strength: The idea is clear.",
"strength: Experiments are conducted on multiple tasks.",
"strength: The paper tries to apply contrastive learning on SPD manifold, and introduces some data augmentation techniques.",
"strength: Experiments show... | 4 |
4JtwtT4nYC | [
"strength: The paper proposes an interesting approach to figure out the performance imbalance across tasks in training through applying the data sampling strategies and and shows empirical improvements on MTRL benchmarks.",
"strength: The paper clearly identifies the task performance imbalance problem in current... | 3 |
nTNgkEIfeb | [
"strength: The high-level idea of the paper is simple: with some modifications (HSIC regularizer in this case), existing model inversion attacks in the standard ML literature can easily carry over to federated settings, where the attackers are malicious clients and the target network is the global, shared model fro... | 7 |
tmsqb6WpLz | [
"strength: The motivation is well-founded and the claims are sound.",
"strength: Experimental analysis is very detailed and explanatory.",
"strength: Paper is clearly presented and easy to follow.",
"strength: The method how the analysis is performed is novel. Creating training and evaluation corpora with con... | 5.75 |
Jd3Vd7GCyq | [
"strength: Clear improvement over previous work.",
"strength: Comprehensive set of results, covering the complexity of problem from various angles.",
"strength: Original technical ideas.",
"strength: Generalization to the non-strict model and strenthening of some hardness and FPT results.",
"strength: The c... | 7 |
PVGS8UZ6GX | [
"strength: The proposed objective MLM-U, though simple, is very effective in improving the performance of multi-step planning for maze navigation.",
"strength: This paper provides a detailed analysis of the convergence speed, and generalization capability of the fine-tuned model, both suggesting that the transfor... | 4 |
HtbqsbNw9c | [
"strength: The paper has a clear structure, and it‘s easy to follow.",
"strength: The idea of modeling the head and shoulder separately is interesting. The neural texture strategy can model the shoulders efficiently with less 3D Gaussians.",
"strength: The pipeline is verified on different human subjects.",
"... | 6.2 |
zIJFG7wW2d | [
"strength: The paper demonstrates the effectiveness of their approach on a fairly exhaustive evaluation. The approach is evaluated on 29 datasets spanning generation, classification and reasoning. The evaluation is run using three LLM baselines.",
"strength: The authors provide exhaustive details about the prompt... | 4.666667 |
anzIzGZuLi | [
"strength: The approach of \"relative magnitude tokenization\" (RMT) is an inventive technique for adapting pre-trained language models to tabular data. This method of converting scalar values to a tokenized format to be perceived as meaningful words within the language model's vocabulary stands out as a significan... | 7 |
gkfUvn0fLU | [
"strength: The analysis of the over parameterization of composite reward functions in interesting and of importance to LLM-Alignment",
"strength: The proposed derivative free optimization method, NM-PPO is novel and computationally efficient.",
"strength: The paper is generally well written and easy to follow."... | 7 |
9XETcRsufZ | [
"strength: Theoretical Foundation: The paper offers theoretical analysis, including formal proofs and establishing clear upper and lower bounds on MoEs' capabilities for both memorization and reasoning tasks. Utilizes communication complexity theory to highlight fundamental differences in parameter scaling and capa... | 7 |
JapY2HtNI5 | [
"strength: RNAformer is a single deep learning model that relies solely on RNA sequence input and does not require additional information like multiple sequence alignments (MSAs), embeddings, or ensemble techniques.",
"strength: Also, the Axial-Attention makes the model to be efficient to the length of RNA sequen... | 5 |
YIls9HEa52 | [
"strength: The paper's originality derives from improvements it makes in the class of AR-HMM and SLDS models by removing exchangeability without removing input recurrence.",
"strength: This enables greater efficiency with expressibility.",
"strength: Overall, this work nicely integrates the heat-equation genera... | 6.6 |
lOi6FtIwR8 | [
"strength: This paper relied on the key observation/assumption that embedding vector $\\approx$ high-frequency vector + toxic vector + context-dependent vector, and then used linear algebra tools including SVD to separate toxic vectors. I think an algorithm to separate toxic vectors based on the factorization of th... | 6.666667 |
FN7n7JRjsk | [
"strength: The significance lies in its potential to reduce the computational burden of fine-tuning large pre-trained models while maintaining performance.",
"strength: The paper is well-structured, and easy to follow.",
"strength: The introduction of FlexRand adds another layer of adaptability to the pruning p... | 6.666667 |
fgaNjiijS1 | [
"strength: An important issue of existing DCT using the MMD has been identified, specifically the MMD can be the same for distributions with different norms in a reproducing kernel Hilbert space.",
"strength: Rigorous theoretical results are provided.",
"strength: Sufficient experiment results are included.",
... | 7 |
bMvqccRmKD | [
"strength: the problem tackled here is difficult and highly relevant. Generalization under variations of the underlying dynamics is an area that has shown little progress",
"strength: paper is well structured, fairly easy to follow and the description of the method appears to be complete",
"strength: I take the... | 7 |
bcTjW5kS4W | [
"strength: The simulations are mostly convincing (see below) of the approach's validity, providing compelling evidence for its use in biological experiments.",
"strength: To my knowledge, apart from [1], this is one of the first actionable use cases of transformer models in systems neuroscience.",
"strength: Or... | 7.5 |
yNyDvFQNEm | [
"strength: This paper proposes a pipeline to reduce the dimensions of node features.",
"strength: The paper appears to propose a novel way to generate clusters through embeddings.",
"strength: The paper's main strength is the novelty of the problem setting. I am not aware of any other approach to clustering tha... | 3.4 |
HXwrppoSPc | [
"strength: The proposed method is well-motivated, and the relationship between the prototypes and the class-defining features is clear. The requirements for intrinsic interpretability that the authors address are essential components of intrinsic XAI approaches.",
"strength: Originality: The paper proposed an ela... | 3.25 |
SwIkknEqmt | [
"strength: The paper identifies and addresses a novel issue, frequency collapse, in Transformer-based time series forecasting models. The proposed PErM strategy is an innovative solution that uses a non-linear remapping layer to enhance the frequency-domain representation of embeddings, offering a fresh perspective... | 4.333333 |
8BJl6LQgW5 | [
"strength: The attention that the authors give to relevant foreground information and moving tiny objects is meaningful for constructing world models.",
"strength: The performance gain of the proposed method is considerable on the Atari 100K benchmark and DeepMind Control Suite.",
"strength: The experimental va... | 5 |
xDrFWUmCne | [
"strength: The paper is well-written and easy to follow.",
"strength: It presents an easy solution to the sampling problem of diffusion models that only requires limited training time while obtaining.",
"strength: The soft teacher loss is effective and simple to implement.",
"strength: The evaluation is thoro... | 8 |
CRmiX0v16e | [
"strength: The paper is well-organized, and the ideas are clearly illustrated.",
"strength: This paper introduces a novel approach for efficient open-vocabulary 3D instance labeling by leveraging 2D bounding box priors from a fast 2D object detector, demonstrating superior performance and time efficiency in exper... | 7.8 |
CblmtAxrRg | [
"strength: Proposed factor profile as the basic construct to perform decision-making instead of full text.",
"strength: Prescribed a way to incorporate LLM outputs into Bradley-Terry models for estimating relative strengths of items and for bayes reasoning and analogical reasoning.",
"strength: The paper introd... | 5.2 |
wJ3GeGLFmc | [
"strength: The paper addresses the challenging task of low-precision, end-to-end training for neural networks.",
"strength: The approach is straightforward and easy to understand.",
"strength: Evaluation results are provided for three different hardware platforms.",
"strength: The paper studies integer traini... | 4.5 |
zB6uMznFuZ | [
"strength: The paper is well-written and well-structured.",
"strength: The paper presents a clear method similar to diffusion methods in other domains. The technical details are discussed in detail. It seems straightforward to reproduce the results.",
"strength: The presented problem is essential and timely. In... | 3 |
jCPak79Kev | [
"strength: The idea of transferring the analog circuit into a sequence-based graph representing is a novel and interesting idea, enabling the use of a generative model for scalable circuit generation.",
"strength: The collection of large-scale analog circuits. It would be great if the authors can release the data... | 7.5 |
DMJNaBUv3D | [
"strength: This paper studies an interesting and important problem of feature redundancy, especially in the context of few-shot learning.",
"strength: This paper provides a theoretical framework that sheds light on the complex phenomenon of feature redundancy.",
"strength: This paper also proposes a novel solut... | 5.5 |
NrLXQWwCMg | [
"strength: The idea of this paper that suppress the unnecessary frequencies and amplify the essential frequencies in Fourier features is novel.",
"strength: This paper addresses the frequency selection and overall model optimization issues by introducing bias-free MLPs and dynamic learning rates, achieving Pareto... | 3.5 |
Fs9EabmQrJ | [
"strength: Embedding LLMs to handle downstream tasks is indeed a fascinating approach! This method allows you to create compact representations of each model that capture its unique strengths and weaknesses, enabling efficient task-specific decisions without running each model on every input. This approach streamli... | 6.666667 |
ff5srKUefm | [
"strength: The capsule and voting process is explained through information theory, making the motivation for the proposed method clearer.",
"strength: Through an entropy voting mechanism that differs from the traditional dynamic routing algorithm in capsule networks, iterations are avoided and the number of parti... | 3 |
LtuRgL03pI | [
"strength: Very solid design choices. The authors clearly have good knowledge of techniques relevant to this problem, and the proposed solution make a lot of sense to me e.g. discretizing object features with VQVAE, discrete diffusion models, the use of MASK for diffusion-based graph generation, various learning tr... | 7.5 |
0Qyxw0cCuu | [
"strength: The proposed three objectives are interesting and helpful.",
"strength: The proof and derivation of the objectives are comprehensive and easy to understand.",
"strength: Extensive evaluations and comparisons to baselines show promising results.",
"strength: The paper investigates a somewhat interes... | 5 |
TTrzgEZt9s | [
"strength: The paper has solid contributions compared to prior work.",
"strength: The theoretical analysis is sound and well supported.",
"strength: The authors also discuss the case where the hypotheses of this work are violated and argue that their algorithm still converges in that case.",
"strength: The em... | 8 |
LBd87fWerd | [
"strength: The paper is generally well-written, with clear explanations of complex concepts such as the gradient-based optimization process.",
"strength: The experimental design is robust, utilizing a diverse array of retrieval models and demonstrating GASLITE's efficacy across different scenarios. This thorough ... | 6 |
uW3tNSx7PZ | [
"strength: The paper addresses an important issue in federated learning - gradient privacy leakage, which is a current research hotspot with significant application value. It explores the role of data augmentation techniques in improving the model's generalization ability and security.",
"strength: The paper prop... | 2.5 |
JXKFPJe0NU | [
"strength: This paper is quite original in its approach to motion planning by adapting the branch-and-bound (BaB) algorithm for neural dynamics (ND) models.",
"strength: Unlike existing methods, which typically rely on sampling-based or gradient descent approaches, this work creatively applies a modified bound pr... | 6.25 |
eciCtsqGc8 | [
"strength: Interpretability analysis on physiological time series",
"strength: The model was tested on two types of physiological time series: PPG and single-lead ECG.",
"strength: To the best of my knowledge, this is the first work that applies generative pre-training to representation learning for heart time-... | 7.333333 |
hVTaXJ0I5M | [
"strength: Summing over items with partial orders is a fundamental problem that has not been fully studied under differential privacy.",
"strength: The proposed algorithm is very time-efficient, only quadratic in the number of bits. The speed-up is significant over some simple sampling algorithms",
"strength: T... | 6.75 |
7IzeL0kflu | [
"strength: The work on simplifying deep reinforcement learning and removing techniques that might not be necessary, like replay buffer and target networks, is undoubtedly fundamental to deep reinforcement research. This has vast implications for rethinking the widely existing deep RL approaches and can help in othe... | 7.5 |
RaR3ETzyKp | [
"strength: The work is well written except for a few typos (for example, in line 198/199 \"To **analysis**\" is written instead of \"To **analyse**\", and in line 309/310 \"have not been **evaluation** on RFM\" is written instead of **evaluated**).",
"strength: The idea is sound and is theoretically motivated, th... | 7.333333 |
mtyYWBx2ZF | [
"strength: The method is clearly presented.",
"strength: The paper compares scores with prior research to ensure consistency.",
"strength: Nicely written intro with a clear motivation and big question",
"strength: Overall the sparse encoding model linking LLMs to the brains is an interesting and topical appro... | 3.75 |
hrqNOxpItr | [
"strength: The framework poses significant progress towards better theoretical understanding on machine learning tasks, particularly classification tasks. If the theory holds, it may have a substantial influence on theories of adjacent research areas as well as many applications. Although this is a theoretical pape... | 8 |
7H1jbTaOIn | [
"strength: This paper highlights the important yet underexplored problem of distributed non-IID in-context learning (ICL), offering fresh insights into a new problem.",
"strength: The paper presents some valuable experimental results demonstrating the poor performance of distributed non-IID ICL under simple unifo... | 5.5 |
Wvi8c0tgvt | [
"strength: Comprehensive experiments have been conducted to demonstrate the effectiveness of the proposed method.",
"strength: The proposed blur image augmentation method could be beneficial to relative research.",
"strength: The paper effectively identifies key challenges in blur data augmentation and addresse... | 6.666667 |
zgs450VzkU | [
"strength: The authors propose to iteratively rewrite the query to improve search results for extensive personalized context, which is a timely problem of interest, with a significant body of literature.",
"strength: The paper handles an important problem around long-context RAG. Their approach of using a conditi... | 3.5 |
ZT33ACedmn | [
"strength: The authors evaluate their method on a large variety of data sets and time series tasks.",
"strength: They also spend a significant amount of the manuscript to describe the inner workings of the ABBA algorithm.",
"strength: Overall, the paper is comprehensible and relatively easy to follow.",
"stre... | 3 |
KJFyOwAnLR | [
"strength: Despite some technical details, the overall logic of the paper is well-written and clear. I can understand the authors very well.",
"strength: This study used monkey physiological data for model training",
"strength: This paper proposes an interesting framework for analyzing the computational proble... | 4 |
jKHmjlpViu | [
"strength: The paper presents a well documented dataset.",
"strength: The dataset seems to be useful for training LLMs of small-medium scale.",
"strength: This paper proposes an open high-quality mathematical dataset, which can let models get a good reasoning ability in a lower computation.",
"strength: This ... | 6 |
9Qptgv0Eyw | [
"strength: The proposed transformer-based method outperforms other DL methods. The performance gain could be a more effective MiT encoder than CNN, the feathering technique when stitching local patches, etc.",
"strength: +++Works better than two NN baseline methods.",
"strength: The paper is written in a logica... | 3.4 |
CuKla49IjN | [
"strength: A new attention architecture is proposed.",
"strength: Experiments are done on three real-world datasets from different areas.",
"strength: The paper propose to model attentions by incorporating contexts",
"strength: The paper targets real-world datasets and applications",
"strength: Context-awar... | 2.5 |
bjxuqI4KwU | [
"strength: This is a very general result on a fundamental model of causality.",
"strength: Originality: The paper is a novel work that discusses the identifiability of the SCM model under different model assumptions.",
"strength: Quality: The paper provides a thorough discussion of the identifiability issue wit... | 7.5 |
lgsyLSsDRe | [
"strength: This work gives a good summary of the STOA NV-Embed model that leads the MTEB benchmark. I think the community will very much appreciate this paper.",
"strength: Impressive experimental results with good ablations to justify the design choices.",
"strength: Clear presentation.",
"strength: Provides... | 7.5 |
ShjMHfmPs0 | [
"strength: The paper is clearly written and easy to follow. Their problem is appropriately formulated in a mathematically sound way.",
"strength: In Section3, a toy example of gaussian models is analyzed, which provides a theoretical evidence for their heuristic Claim in Section 2.",
"strength: It is predictabl... | 6.666667 |
nE3flbe88p | [
"strength: The paper is well-written and easy to understand.",
"strength: TeamCraft is more comprehensive than previous benchmarks together with substantial demonstrations.",
"strength: Multi-agent collaboration is an important research problem, with algorithms applicable in a wide range of real-world scenarios... | 3.25 |
YCu7H0kFS3 | [
"strength: This work seems to be the first application of activation steering to improve the diversity of decisions of LLM agents in sequential decision-making scenarios.",
"strength: The proposed technique is able to effectively increase the entropy of the action distribution of the LLM policy, which could not b... | 4.75 |
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