paper_id stringlengths 10 10 | items listlengths 4 82 | gt float64 1 9.5 |
|---|---|---|
skHPtDnYGa | [
"strength: The idea is intuitive and easy to understand.",
"strength: Rethinking the impact of the LLM backbone in MLLM evaluation is insightful and may advance the development of MLLM.",
"strength: The paper is generally easy to read and follow.",
"strength: The introduced metrics and RAG pipeline are sound.... | 4.5 |
Q0s6kgrUMr | [
"strength: The method proposed in this paper differs from traditional causal discovery algorithms, providing a new direction for high-dimensional causal relationship detection.",
"strength: The effectiveness of the RoCA method is demonstrated through theoretical analysis and validation on multiple datasets.",
"... | 6.666667 |
ymqLAmqYHW | [
"strength: The topic of backdoor attacks and defenses is important.",
"strength: The writing in the paper is easy to follow.",
"strength: The experimental setups are comprehensive, and the results look good with appropriate replications.",
"strength: Proposes a novel and effective backdoor attack strategy.",
... | 4.5 |
tmwR707odU | [
"strength: The motivation to balance the role of LLMs and GNNs in a fine-grained sample-wise manner for TAG learning is straightforward and convincing.",
"strength: Writing is clear and easy to follow. Pseudo code is present to assist better understanding of the mechanisms designed.",
"strength: The integration... | 4.5 |
uvHmnahyp1 | [
"strength: The background and related work section was strong, and covered the previous work in this domain well.",
"strength: The paper, including the appendix, was well-structured and easy to follow.",
"strength: The use of the GFlowNet improves both diversity and high reward modes compared to other optimizat... | 7.5 |
3GDKJSQnW2 | [
"strength: This paper proposes a novel approach to text-based video dynamic editing",
"strength: The video frames shown in the paper demonstrate edited motion similar to the text-prompt inputs.",
"strength: Unlike previous video editing approaches, which mainly focus on simple edits like appearance and style, t... | 5 |
hVpAjJPfgZ | [
"strength: The paper focuses on increasing the input window dimensionality, which is also an active research are in LLM research",
"strength: The paper introduces a novel approach to overcoming the Lookback Window Limitation (LWL) in long-term time series forecasting, which is a significant research contribution.... | 3.25 |
VyMW4YZfw7 | [
"strength: Addressing the use of simpler methods to match and outperform complex DNN-based architectures.",
"strength: Originality: The paper presents a novel perspective on Graph Neural Networks (GNNs) by arguing that many current GNN architectures are over-engineered and that traditional, simpler methods can ac... | 3 |
MyotJECv0D | [
"strength: This is a thorough study that covers many different correlation measures, metrics variations, as well as language pairs.",
"strength: The data setup is a Chinese-centric one, which offers a novel perspective on top of many existing English-centric studies.",
"strength: The choice of languages within ... | 2.5 |
puGvShnqeA | [
"strength: Using Deep Linearly Gated Networks (DLGN) for studying and interpreting adversarial attacks is, to the best of my knowledge, novel.",
"strength: The observation that adversarially trained models exhibit higher gate overlap on clean images is an interesting finding.",
"strength: Studying an important ... | 3 |
HnhNRrLPwm | [
"strength: The MMIE benchmark presented in the paper offers a significant contribution in the interleaved comprehension and generation domain. The benchmark is of significant scale (~20k examples) and well categorised, specifically the project-based learning, situational analysis and multi-step reasoning categories... | 8 |
fMaEbeJGpp | [
"strength: Integrating multimodal retrieval into vision-language models is intuitive.",
"strength: Document question-answering is a critical task, and the use of large models aligns well with current technological trends.",
"strength: Introducing multiple modalities to improve answer accuracy in document questi... | 2.5 |
nM2kuesKpC | [
"strength: D2P2-SGD nicely consolidates several existing methods and I appreciated the “unified framework” angle (line 247).",
"strength: The theoretical analysis applies to a general setting, with utility bounds and convergence rates for both convex and non-convex functions.",
"strength: The authors provide a ... | 3 |
AUCYptvAf3 | [
"strength: This paper provides a very thorough discussion of how to combine MAPF algorithms with diffusion models and demonstrate its ability to scale to multi-agent settings.",
"strength: The experiment setting is diverse with varying levels of difficulties.",
"strength: The writing is clear and structured and... | 7.5 |
02Od16GFRW | [
"strength: The work show the emergence of equivariant in ensemble models",
"strength: The work generalizes previous works where the proof relied on NTKs",
"strength: Experiments with large ensemble of models show the emergence of equivariance",
"strength: It generalizes the results in Gerken & Kessel",
"str... | 5 |
BgxsmpVoOX | [
"strength: The proposed rare-to-frequent prompt rewrite is novel and effective in terms of generating rare-concept-images.",
"strength: The empirical results looks promising.",
"strength: Solid empirical results are provided to validate the effectiveness of the method.",
"strength: A new benchmark, RareBench,... | 7.5 |
xNCDKQMPYD | [
"strength: The paper presents a training-free method of generating linear combination of merging multiple LORA trained weights, utilizing GPT4o.",
"strength: The paper shows qualitatively that these approaches offer a better and cheaper method to controlling the characteristics of the generated image.",
"streng... | 3.5 |
zcx6rIMbbR | [
"strength: The paper presents the clear motivation that the performance of fine-tuning on the adjusted quantized models is even worse than using the original quantized models directly.",
"strength: Low-precision models fine-tuned with QR-Adaptor can surpass the 16-bit fine-tuned models, while maintaining memory u... | 5.4 |
szRmEM8Kx5 | [
"strength: Basic research into embedding spaces is important and underexplored. Temperature is a similarly crucial and \"taken-for-granted\" value for practitioners training models with contrastive loss.",
"strength: The result that temperature decreases retrieval performance and increases clustering performance ... | 7.5 |
UHg1xTRzZK | [
"strength: The paper successfully did what they proposed, improving the translation performance with the proposed method can significantly reduce the damage in general instruction-following tasks.",
"strength: The authors propose a straightforward method for LLMs to learn the translation task (in this study) with... | 5 |
OTFKVkxSlL | [
"strength: This paper tries to solve an important problem in Diffusion-model-based offline MARL, that is, the use of the centralized training with decentralized execution (CTDE) paradigm. As noted in [1], this is a research gap in this field.",
"strength: The algorithm design is simple yet effective, which is dem... | 6 |
JetCx7Tpgb | [
"strength: The idea of introducing orthogonal constraints during training seems interesting, which may provide useful insights for future research.",
"strength: The experimental results are comprehensive and effectively validate the superiority of the proposed methods across various datasets.",
"strength: The a... | 4.2 |
wwXgvjNmt5 | [
"strength: The proposed benchmark is useful for specific fields like journal and advertisement industry.",
"strength: Many popular models are tested, which is good.",
"strength: This paper’s structure is clear.",
"strength: This paper is well-written.",
"strength: This paper firstly introduces an benchmark ... | 4 |
BgcapX9ers | [
"strength: The authors demonstrated that their framework in a partial observability setting achieves results comparable to those obtained with perfect knowledge.",
"strength: The new dataset introduces more complex scenarios, which is evident from the performance gap. However, additional details about these scena... | 5 |
glgvpS1dD1 | [
"strength: The framework is well-supported by theoretical derivations, including generalization bounds for adversarial PEHE loss.",
"strength: Experiments on both synthetic and real-world datasets are conducted, demonstrating the model's robustness and effectiveness.",
"strength: The paper studies an interestin... | 4.5 |
SBj2Qdhgew | [
"strength: This paper provides a novel \"solution\" for unfairness in federated learning. Even if this issue has been extensively studied, there has been few work attempting to investigate the fundamental root that causes unfairness, let alone giving a theoretical explanation. This work uses a mathematically rigoro... | 7.333333 |
UJeIujVxMn | [
"strength: The FedEBA+ algorithm addresses the accuracy-fairness trade-off issue. The extensive results on four datasets show that FedEBA+ reduces variance without compromising the performance of clients.",
"strength: An ablation study highlights the advantages of the proposed aggregation approach of FedEBA+. Spe... | 5.333333 |
I2ZYngkRW6 | [
"strength: Combines AT with NAT in a novel way",
"strength: Achieves State-of-the-art performance",
"strength: Comprehensive benchmarking",
"strength: Detailed experiments",
"strength: Approach shows better empirical performance than baseline approaches",
"strength: Combining the strength of both non-auto... | 4.25 |
VkWbxFrCC8 | [
"strength: The performance gain over the previous attempt in this direction (i.e., COMBINER) is indeed very impressive. The innovations introduced in this paper seems to make the combiner-like approach a competitive paradigm for INR-based data compression.",
"strength: All three proposed modifications are technic... | 6.666667 |
yuy6cGt3KL | [
"strength: The problem the authors are addressing is important.",
"strength: The authors correctly point out that much evaluation in the literature is lacking, often performed on synthetic data and comparing to only a small subset of other methods.",
"strength: The authors overall approach is very principled an... | 7.25 |
E0UsEIRBQ8 | [
"strength: This paper proposed a novel underwater image enhancement method guided by attribute-based data distribution (UIEG+), which aims to reduce distributional differences between enhanced and unlabeled underwater images by analyzing the distribution of unlabeled images in terms of color and scale attributes.",... | 3 |
6lB5qtdYAg | [
"strength: The writing is clear to understand with detailed formulations and figures.",
"strength: The results are superior when compared to other methods.",
"strength: The phenomena of Appendix B are very interesting, revealing that the original model maintains a similar visual pattern from other parts of imag... | 6 |
kRoWeLTpL4 | [
"strength: The approach is novel and sound: CP-Fuse introduces the more explored inference-time model fusion techniques to the recently emergent challenges of copyright infringement prevention, the application is novel and the problem addressed is important. The efficacy of the method is justified with both theoret... | 7.5 |
OFWD0jgJ17 | [
"strength: This paper applys GNNs in combination with SCL to address class imbalance in geodemographic data, which is a relatively unexplored approach in the field.",
"strength: This paper leverages real-world census data from 2011 and 2021 for England and Wales.",
"strength: This paper aims to improve classifi... | 3.5 |
jZsN9zo8Qi | [
"strength: There are no resources (as far as I know of) to study and characterize _long-context_ interleaved image-text comprehension or empirical studies of this comprehension ability. This is one of the first.",
"strength: The experimental evaluation is broad, covering multiple vision language models including ... | 6.5 |
iC4hBE9xYe | [
"strength: The paper is well laid out and easily readable.",
"strength: The appendix has been arranged in a way that makes it easy to follow.",
"strength: The biggest strength of the paper is the novel contributions that it has.",
"strength: Most prior literature in RL (especially average reward RL) considers... | 4.75 |
uuef1HP6X7 | [
"strength: This paper trains a diffusion model to predict material properties from color images, demonstrating strong performance compared to previous methods.",
"strength: Extensive experiments validate the approach, showcasing its effectiveness across various applications.",
"strength: The paper is well-organ... | 6.6 |
99YEbiBbdy | [
"strength: The paper is well-written and very clear, including the proofs.",
"strength: The motivation of wanting to consider structural assumptions that go beyond the manifold hypothesis is sound.",
"strength: While the MRF assumption is certainly idealistic, the authors suggest in their conclusion that ultima... | 6.75 |
p4JeJ9uhEL | [
"strength: The investigated problem of camouflage animal detection is interesting.",
"strength: The contribution of dataset is good, though the construction procedure involves quite some manual effort, thus limiting its scalability.",
"strength: The writing is clear, especially on the dataset curation part.",
... | 4 |
84n3UwkH7b | [
"strength: This work builds on a very simple and clever observation that the impact of text prompt on the generation by a diffusion model can be used for detecting if a particular generated image was memorized.",
"strength: The method is extremely fast and can even detect memorization with a single step. Further,... | 8 |
YhfrKB3Ah7 | [
"strength: The paper is well written and easy to understand for the most part.",
"strength: The proposed method is a novel and interesting application of amortized learning/BO for PBO setting. The empirical results seem superior than traditional PBO methods and acquisition functions.",
"strength: Nice set of ex... | 7.4 |
fkKW1PK8Ga | [
"strength: They designed an algorithm focused on enhancing the generalization ability of gradient descent, leveraging the concept of a generalization ratio and insights from reinforcement learning.",
"strength: They experimentally demonstrate that the algorithm outperforms traditional gradient descent.",
"stren... | 5.25 |
LYHEY783Np | [
"strength: The paper proposes a new neuron manipulation method that effectively induces diferent personality traits in LLMs by providing two prompts with contrasting personality levels. The approach also demonstrates the feasibility through three different evaluations.",
"strength: The paper is clearly written, w... | 6.666667 |
yzloNYH3QN | [
"strength: The writing of this paper is well-crafted, allowing readers with relevant backgrounds to quickly follow and provide feedback.",
"strength: The proposed method is versatile and applicable, making it suitable for use with open-source LLMs.",
"strength: The problem is important, and the overall writting... | 5 |
AAZ3vwyQ4X | [
"strength: It presents a flexible framework that can incorporate different modality as inputs, incorporating various loss functions and clustering objectives",
"strength: It addresses a real-world problem in epidemiology (using MALDI data as a cost-effective alternative to WGS)",
"strength: It introduces a new ... | 2.5 |
H4iVLvRusn | [
"strength: This paper formulates the KD problem as a bi-level optimization through the perspective of IOT. Building on the IOT-based formulation, this paper further proposes novel closed-set and open-set SelKD methods that allow the student model to learn specific knowledge from assigned tasks, making SelfKD well-s... | 6 |
BZwXMqu4zG | [
"strength: The results appear promising and solid.",
"strength: The experiments are thorough.",
"strength: The writing is easy to follow.",
"strength: The paper is well-organized and easy to follow.",
"strength: The method employing motion guidance is logically sound, and the experimental results showing im... | 6 |
JOBokGDcX0 | [
"strength: The paper is unique and interesting.",
"strength: It explores alternatives to commonly accepted overlapped chunking for long speech sequences.",
"strength: The proposed techniques achieve a significant reduction in runtime and memory usage for two different tasks: speech separation and audio super-re... | 2.5 |
5pd46nlxc6 | [
"strength: Solving practical issues. The paper introduces an asynchronous learning structure that addresses the temporal inconsistencies and update delays inherent in synchronous approaches. This enables agents to update independently, significantly improving learning efficiency and environmental adaptability. This... | 4.666667 |
B0jjj5RiAQ | [
"strength: The paper introduces LEAP, a method for black-box prompt learning that does not require a predefined label vocabulary, offering a new solution for optimizing LLMs in scenarios with limited access to model internals.",
"strength: LEAP is presented with a clear structure, detailing an alternating optimiz... | 3.5 |
NUD03NBDOE | [
"strength: The paper studies an important but overlooked problem of evaluating RAC capabilities of LLMs in a systematic way, beyond measuring surface RAC. The paper demonstrates through the difference in performance on basic fluents and the ramification fluents, that this is indeed a weakness of current LLMs.",
"... | 6.75 |
DJSZGGZYVi | [
"strength: The paper’s key finding—that self-supervised representations, like those from DINOv2, can serve as a teacher to distill base features in a diffusion model—is both novel and insightful. By using these high-quality representations, the diffusion model can more quickly learn a robust semantic foundation, al... | 9 |
RC2h1WQvPo | [
"strength: The paper is well-written and well-presented.",
"strength: Although learning an interpretable latent space using space-filling vector quantization has been introduced in another previous work, its application to GANs is novel and interesting.",
"strength: The proposed method can be applied to pre-tra... | 3.666667 |
qyU5s4fzLg | [
"strength: Overall, the paper is strong, and the proposed method is a fundamental improvement in unsupervised parsing. In addition to providing strong results, it provides insight into what is missing in log likelihood maximization and how one might augment log likelihood with other objectives.",
"strength: The e... | 7.5 |
dM1wO2OkbO | [
"strength: Introducing simplified new architectures can help elucidate the performance of the most advanced systems; for example the match between the training behavior of the transformer and their model is very interesting.",
"strength: Newer, simpler architectures can also be more amenable to theoretical analys... | 6.333333 |
sruGNQHd7t | [
"strength: The paper addresses the privacy issues in deep learning and proposes a privacy-preserving strategy that users can implement independently, without requiring any modification to the deep learning models.",
"strength: The key idea by leveraging the encoder and decoder is intersting and clear.",
"streng... | 3 |
3cuJwmPxXj | [
"strength: Important problem. Can be thought of as OOD estimation of intervention effects through learning latent representations.",
"strength: Extremely well written paper!",
"strength: Crucially E[Y | do(A=a')] \\neq E[Y | A=a'] for a' not in support of A.",
"strength: The propositions are exactly at the pl... | 8 |
j87C29mAZl | [
"strength: The presented methodology introduces a novel approach that effectively addresses the known limitations of Looped Transformer model architectures.",
"strength: The paper provides a robust background, thoroughly reviewing previous studies in the field.",
"strength: It includes rigorous mathematical dem... | 5.666667 |
ywHOnGOLb1 | [
"strength: Generality and Flexibility: The proposed framework is designed to be generic and can be seamlessly integrated into existing double-actor DRL methods as well as extended to multi-critic DRL methods. This broad applicability enhances its potential impact on the DRL community.",
"strength: Improved Policy... | 4.666667 |
RrIjnSMhMZ | [
"strength: Overall the manuscript reads quite coherently.",
"strength: The author’s proposition of defining constraints as opposed to target specifications is an interesting approach for addressing design problems.",
"strength: By having fewer specifications, it seems plausible the authors framework could offer... | 2.5 |
IuXR1CCrSi | [
"strength: It is a valuable problem for encoding graph-structured data as text for LLMs.",
"strength: Many factors are taken into considerations, and detailed analyses are provided.",
"strength: The findings provide valuable insights into strategies for improving LLM performance on graph reasoning tasks.",
"s... | 6 |
HnpDHiItd2 | [
"strength: This paper addresses the limitation of the previous diffusion model approach, i.e. the temporal dependencies of actions, by using generated intermediate visual supervision.",
"strength: The Latent Space Temporal Logical Interpolation Module seems to be helpful as the intermediate visual supervision.",
... | 6.666667 |
vQIVbfTMzf | [
"strength: This paper is a nice exercise in basic statistics and probability.",
"strength: The proofs seem to be correct.",
"strength: The paper tackles a fundamental and ubiquitous problem in statistical learning, i.e., robust mean estimation. It does so by providing an optimization method that is shown to be ... | 3.25 |
dIaykjbiiL | [
"strength: Variety of the datasets in the experiments. The authors evaluate their method on a wide variety of datasets.",
"strength: It is good that they have suggested to use a wide array of signals for the synthetic data generation.",
"strength: The goal is important: of generating simulated data to aid in le... | 2.5 |
AgM3MzT99c | [
"strength: The paper is well motivated and the problem is interesting. They correctly identify one of the fundamental issues with open-ended learning algorithms, i.e. that if the agents choose tasks based on novelty, feasibility or information gain alone, they may end up choosing tasks which are completely unintere... | 6.25 |
O9YTt26r2P | [
"strength: Arithmetic tasks are a particularly useful test bed to understand the learning mechanism of LLMs. However, it has been an open question as to what algorithm the model is truly learning. This work makes an important step in this direction, particularly since it applies to the newest edition of LLMs.",
"... | 6.8 |
Go33RnNiVH | [
"strength: The paper studied diverse exploration, which is an important topic in RL.",
"strength: The proposed method makes intuitive sense, and the way to construct diverse policy set based on interpolation between pi_cov and pi_cor is a reasonable approach.",
"strength: There are experiments that demonstrate ... | 4 |
I6UbnkUveF | [
"strength: The paper addresses the problems of finding the global optimum of GP posterior samples efficiently, which is an important topic for many BO acquisition functions.",
"strength: There are many empirical analyses for the proposed methods.",
"strength: The method significantly reduces the CPU times to op... | 7 |
hNjCVVm0EQ | [
"strength: The paper is well written, the ideas are clearly formulated, and the results are well presented.",
"strength: To the best of my knowledge, it is the first time that these two methods have been combined and applied to model time-varying systems. Thus, it's a novel and original approach.",
"strength: T... | 7.5 |
DzGe40glxs | [
"strength: The investigation of emergent planning using a concept-based interpretability approach is original and interesting.",
"strength: The paper is of high scientific quality, the experiments are rigorous, hypothesis driven and the conclusion (in the affirmative) is well backed-up.",
"strength: The paper i... | 8 |
Bo62NeU6VF | [
"strength: Reflection-based Defense Yields More Flexibility: The proposed method has significant flexibility compared to other methods. With proper prompting, unlike traditional filter-based adversarial attack defense, it is easy to use a safe backtracking model with updatable preference and knowledge, depending on... | 8 |
vM4CdVScT8 | [
"strength: The paper is well written and wasy to understand.",
"strength: The central idea is a simple, effective and intuitive technique to increase the efficacy of current quantization methods.",
"strength: They showcase their method on various modern data domains of interest (datasets, LLM layers and KV cach... | 4 |
lpt4ADbacU | [
"strength: The algorithm is motivated by real-world applications, with a careful illustration of the objective design.",
"strength: The sample efficiency and sparsification efficiency are justified with theoretical analysis and empirical results on various tasks.",
"strength: The problem is of considerable prac... | 4 |
mypnFcBbz4 | [
"strength: Proposed approach incorporates both elements of structural proximity and equivalence into a single embedding for dynamic networks, which has not been done before, to the best of my ability.",
"strength: Proposed approach seems to be technically sound.",
"strength: Paper is well written and easy to un... | 3.75 |
FYvZCwdb6F | [
"strength: VTS: By focusing on the rate of engagement growth (velocity) and using user follower count (mass), VTS captures virality dynamics more effectively than static metrics like total likes or retweets.",
"strength: Practical Relevance: Given the increasing concerns over misinformation and biased content on ... | 3 |
r5IXBlTCGc | [
"strength: Strong communication of the problem and proposed resolution",
"strength: Detailed data generation for both already-resolved experiments and an open-ended future forecasting benchmark",
"strength: Extensive discussion of decisions & limitations",
"strength: Principled theory and evaluation.",
"str... | 7.25 |
tc90LV0yRL | [
"strength: CTFs are not new tools for LLM evals, e.g. Phuong et al. (2024) and concurrent work by Anurin et al. (2024) have used them before; but their potential for assessing LLM offensive cybercapabilities is not yet fully realized so the contribution is still very meaningful",
"strength: using first-solve-time... | 8.666667 |
QstnrTlPyr | [
"strength: I like the general concept, there are myriad types of data that can be used for biological sequence modeling, and I'd like to believe that being smart about data/modality selection can lead to increased performance with fewer parameters/FLOPs by leveraging multiple types of information at once.",
"stre... | 3.666667 |
uvZDQvjULn | [
"strength: The proofs and experimental results in Sections 4 and 5 are well written and easy to read within each section.",
"strength: Reward dropout is a very simple and effective strategy used to enhance decode-time fine-tuning.",
"strength: CLMs are a common biobjective function, and making the connection to... | 6 |
Ty7xx0pn0a | [
"strength: The authors propose coupled dynamics and MPC layer updates instead of decoupled updates in Diff-MPC, which offers better empirical performance, smoother gradients and leverages warm-starting. The combination of DEQ and Diff-MPC is novel.",
"strength: The authors conduct diverse ablation studies to prov... | 4.6 |
BJfIDS5LsS | [
"strength: Unlearning is an important field, which will be necessitated as privacy regulations and \"right to be forgotten\" requirements become more prevalent in real-world ML applications",
"strength: The approach of using MARL for unlearning is (to my knowledge at least) novel",
"strength: Evaluations cover ... | 2.5 |
WjPK2gj0xu | [
"strength: The paper offers several clear illustrations that is greatly helpful in understanding the mechanisms of parameter merging, expansion, and retention.",
"strength: By decoupling the merged task vector and mask, the model can utilize parameters approximating to specific modality to process corresponding m... | 5.5 |
xGs7Ch3Vyo | [
"strength: The paper is well-organized, with a clearly defined objective and comprehensive experimental comparisons, making it accessible and straightforward to follow. I enjoyed reading the paper.",
"strength: Paper (in general) is well-written and easy to follow (even though there are still small things that re... | 7.5 |
SFCHv2G33F | [
"strength: The main strength of the paper is the significant performance boost over the SOTA PocketMiner approach.",
"strength: As the authors allude to, protein language models have shown great success in computational studies of protein structure and function, and this work is another example where pre-trained ... | 3.5 |
KUz8QXAgFV | [
"strength: The presented idea of how to extend pretraining to capture both AR and MIM setup is simple, if it overperforms existing methods or its inference flexibility can be shown to be usable to new setups, I would consider it to be a valuable contribution. IMO as it currently stands it is misleading (see weaknes... | 5.5 |
lnVPfgRnIV | [
"strength: From the perspective of compression and sparsity, the paper is well-motived and proposes a loss function that can be used in many baselines.",
"strength: The compression-sparsity approach is well-motivated. Promoting sparse and separated feature distributions provides a compelling way to prevent knowle... | 4.75 |
bsXxNkhvm6 | [
"strength: A detailed dataset is introduced in this work with clear",
"strength: Detailed experimental setups are provided to enhance reliability of the results.",
"strength: The study built and tested a large number of models.",
"strength: The paper is sound in terms of its application of machine learning me... | 2.6 |
rto6aU453A | [
"strength: Important problem in high-dimensional action selection: The paper addresses a significant challenge in RL—efficiently selecting actions in high-dimensional spaces. In fields like robotics and healthcare, RL applications often involve large action spaces with many redundant or minimally influential action... | 4.75 |
Pc8AU1aF5e | [
"strength: Method is intuitive and effective",
"strength: Experimental setup is useful. It is useful to have one standard benchmark with extensive comparison to baselines and one realistic benchmark on which more qualitative advantages like generalization are shown.",
"strength: Results are promising - the simi... | 7.333333 |
0Q1mBvUgmt | [
"strength: The article is well-written, easy to read, the literature review is substantial and well-organized.",
"strength: The conducted experiments are appropriate for the forecasting problem.",
"strength: An ablation study is performed to demonstrate the method's significance.",
"strength: The appendices c... | 3 |
8sSqNntaMr | [
"strength: The paper presents a novel framework of directly using human preference data, as opposed to reward models, to route between a pair of LLMs.",
"strength: The empirical evaluation is comprehensive, touching multiple architectures, LLMs and common benchmarks.",
"strength: Both metrics of \"average perfo... | 6.333333 |
JbPb6RieNC | [
"strength: Nice paper. This work is comprehensive, provides significant contributions, and is well-written.",
"strength: The biggest contribution is StreamBench. Previously, there was no suitable benchmark for streaming video understanding. StreamBench is a high-quality addition.",
"strength: Furthermore, Strea... | 5.8 |
wkbx7BRAsM | [
"strength: The idea of performing in-context autoregressive video generation is interesting and I have not seen it being done before. Autoregressive video generation without text is very difficult, and this approach seems to address some of the difficulties.",
"strength: The paper is clear and easy to read. The p... | 7 |
X7EMiddusV | [
"strength: The paper proposes a synergistic simulation-machine learning approach to an important problem in metabolic engineering, by combining Flux Balance Analysis, a linear programming-based approach for simulating the steady-state of a metabolic network, with a graph Transformer architecture. The Transformer pa... | 4.666667 |
uxVBbSlKQ4 | [
"strength: By utilizing Gaussian process to the conditional flow matching, the model reflects the temporal dependencies of the given time series data better.",
"strength: The model enables both unconditional and conditional generations.",
"strength: By conditional prior sampling, the unconditionally trained mod... | 6.75 |
tu3qwNjrtw | [
"strength: The paper conducts experiments on various methods and compositions on multiple models to provide a deeper insight.",
"strength: The method proposes metrics that correlate with the effect of a composition.",
"strength: The presentation is lucid and easy to follow.",
"strength: The codebase will be u... | 5.8 |
yeeIGM3N6w | [
"strength: An output based similarity metric of expert clustering is proposed, which is more effective than previous works.",
"strength: The experimental results compared with the previous methods are very good.",
"strength: HC-SMoE offers a practical solution for reducing parameters without the need for retrai... | 5.5 |
cqU91W3LnB | [
"strength: The paper presents the efficacy of retrieval augmentation for new data generation.",
"strength: The proposed method demonstrates improvement over baseline methods.",
"strength: Data Diversity: ReBase enhances data diversity by retrieving data from multiple online sources",
"strength: Reasoning Dist... | 4.333333 |
l6QnSQizmN | [
"strength: The paper is well-written and easy to read: the introduction is thorough, the related works section is exhaustive, preliminary and the LCPO sections provide adequate details, and the methodology section is well-presented.",
"strength: The specific kind of non-stationary problem that the paper considers... | 7.25 |
Sx7BIiPzys | [
"strength: The paper is well-written and easy to follow in most parts. Moreover, the work is well-motivated and I enjoyed that the authors brought back old ideas to the BDL community, e.g., using the discriminant analysis as a likelihood model.",
"strength: I believe the exposition of the method is well done in m... | 5.75 |
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