paper_id stringlengths 10 10 | items listlengths 4 82 | gt float64 1 9.5 |
|---|---|---|
52fz5sUAy2 | [
"strength: The introduction of the neighborhood effect in mitigating bias in Recommender Systems (RS) is innovative. The research addresses a significant issue, and its rationale is evident.",
"strength: The paper is well-structured and the method is substantiated by robust theoretical foundations.",
"strength:... | 6.75 |
wISvONp3Kq | [
"strength: The paper is well-written and presented. The theoretical results seem sound and the approach seems novel. As I perceive it, the introduction of the proposed bilevel optimization, coupled with the utilization of ordinary differential equations (ODEs) and partial differential equations (PDEs) to address th... | 7.333333 |
fqtaADSGEe | [
"strength: The paper proposes a large-scale referring expression dataset and an LLM-based data generated pipeline.",
"strength: The paper also identifies some error cases in previous datasets.",
"strength: A large number of methods are collated and evaluated in this paper, which is very impressive.",
"strengt... | 3.666667 |
q3WzT2mrhB | [
"strength: The authors propose the first dataset for WiFi-based multi-person 3D mesh reconstruction. At the same time, this is also the first paper that studies to use sparse CSI for 3D human mesh reconstruction. So I think this paper definitely benefits future research in this area",
"strength: The proposed meth... | 4 |
i2Phucne30 | [
"strength: Overall, the paper is well-written and organized, which allowed to compactly describe a number of various contributions.",
"strength: Formulation and explanation of a new phenomenon. It is done via a nice illustration (Figure 1, both a. and b.), intuitive explanation of the phenomenon, clear definition... | 7 |
Im2neAMlre | [
"strength: Proper comparison with previous works",
"strength: Through evaluation of the proposed metric and the dataset",
"strength: The authors have proposed a new benchmark dataset to highlight the issue of evaluation across multiple templates",
"strength: Furthermore, the authors propose a new metric for e... | 7.333333 |
E78OaH2s3f | [
"strength: The CAS method's universality across different modalities and its training-free nature are significant advantages.",
"strength: The proposed framework is principled and reasonable.",
"strength: I really liked this paper, it presents an interesting problem and a narrative on how the problemd was solve... | 8 |
7rq2OzkJg3 | [
"strength: Information among similar clients are utilized.",
"strength: local model aggregation is somehow effective.",
"strength: The paper introduces FedSimSup, a new method in personalized federated learning that incorporates a local supervisor to refine personalized models.",
"strength: FedSimSup allows f... | 3 |
JMgxtZqkvO | [
"strength: The article validates the proposed method with extensive experiments on both vision and language tasks, which helps in establishing the robustness and applicability of the technique across different domains.",
"strength: It provides a comprehensive comparison with existing state-of-the-art methods like... | 4.5 |
hgv11VQnIk | [
"strength: The paper makes some useful contributions for subsequent work, such as a list of desiderata for jailbreak evaluation, and a dynamic jailbreak prompt generation approach, with a somewhat novel optimizer module to ensure no stagnation in generated attacks.",
"strength: The optimizer design is also somewh... | 4.75 |
doBof19Ia4 | [
"strength: This paper tackles RNA inverse folding problem, which is an important problem in structural biology",
"strength: The results demonstrate that the proposed method substantially outperforms the baselines",
"strength: Interesting chimeric architecture as shown in Figure 1. The pipeline may work better, ... | 2.6 |
B4nhr6OJWI | [
"strength: I really enjoyed this paper - it takes the observation from the mechanistic interpretability literature that deep networks learn subnetworks to solve specific tasks and uses it to derive a simple method for extracting these subnetworks (essentially by optimizing a sparsity mask over the parameter on a di... | 6.666667 |
lsvGqR6OTf | [
"strength: The motivation is good: rigorously understanding the expressive power of GNNs is a significant direction, especially it requires carefully quantify expressive capacities with sizes and depths. This work follows this motivation.",
"strength: A rich family of activation functions is considered (such as a... | 7 |
fBSc0c1IXJ | [
"strength: This paper considers a common challenge in real-world applications: an agent may not receive prompt feedback when taking action.",
"strength: The paper introduces the novel concept of remote reinforcement learning under communication constraints, a setting not extensively explored in the literature.",
... | 3 |
XfWJT3BUmX | [
"strength: The paper explores a new neural architecture based on points instead of voxels.",
"strength: The experiments presented in the paper show similar performance to SOTA method based on sparse voxels and transformers.",
"strength: Most of the design choices are ablated on the experiments section.",
"str... | 4.4 |
9W6Z9IeLzc | [
"strength: The paper is well written and easy to understand",
"strength: The theoretical section is clear with well-defined notations used consistently through the manuscript.",
"strength: The paper is well written and easy to follow",
"strength: The paper focuses on an important aspect of using cross-task ex... | 5.25 |
mMPMHWOdOy | [
"strength: Strong Results — I put a lot of premium on this strength and use this to justify my overall rating. Many of the gains from training on Math Evol-Instruct are more than 10 points. More importantly, it is quite impressive to design something that outperforms strong proprietary models, so if this method is ... | 8 |
k7Q28aNVko | [
"strength: This paper provides a comprehensive empirical comparison between spectral augmentation-based and edge perturbations-based graph self-supervised learning methodologies.",
"strength: Experiments demonstrate that simple edge perturbations perform as well or outperform more computationally complex spectral... | 4.4 |
BeuTCoe3bf | [
"strength: Both theoretical analysis and experimental support are provided to show the advantages of the proposed methods.",
"strength: The model design is quite simple yet the results are impressive, both in terms of effectiveness and efficiency.",
"strength: The proposed method shows high performance compared... | 5.333333 |
nyuaoVnVCa | [
"strength: The review of the previous works regarding emergence of language is well organized.",
"strength: The overall analysis and statement of made assumptions seem sound",
"strength: The visualization of the guessing game are indeed nice",
"strength: There is some formal grounding of the paper, ie technic... | 2.333333 |
OL44KtasKc | [
"strength: The contributions of this work are well motivated.",
"strength: The proposed method seems to be novel although I am not an expert in this field.",
"strength: The experiments are quite extensive, covering two different GPUs (RTX4090 and RTX3090), representative models for language, image, and video ge... | 7 |
L6r9t0HtqQ | [
"strength: The paper is dedicated to the utilization of target domain-specific information to improve the domain generalization ability of the model, and the proposed method is able to better determine whether a piece of information is present in the target domain or not, compared with the previous methods.",
"st... | 4 |
1oijHJBRsT | [
"strength: The paper proposes a method for generating diverse, high-quality instruction datasets using a baseline LLM that does not require an external, more powerful LLM.",
"strength: The instruction-tuned models so created are better than models trained on small, human-curated corpora and competitive with model... | 8 |
xcHIiZr3DT | [
"strength: This work introduces an approach to extract pseudo-tactile information from vision and contact locations for robotic grasping tasks. The topic is interesting, the pipeline is presented with details, and the experiment results show the effectiveness of the approach with high accuracy.",
"strength: Open-... | 2.5 |
EbWf36quzd | [
"strength: The paper provides a detailed recipe for training scalable transformers, positioning Lumina-T2X as a practical model for the community to adapt for diverse multi-modal applications.",
"strength: The paper provides an in-depth walkthrough of the architecture, clearly explaining each component’s role and... | 7.2 |
762u1p9dgg | [
"strength: Efficient training and inference for LLMs is an impactful topic if done correctly.",
"strength: The idea of doing a mixture of dynamically determined mask with as an MoE alternative is novel and interesting.",
"strength: Description of the method is clear.",
"strength: Nice results beating some bas... | 3.4 |
MJksrOhurE | [
"strength: The architecture design seems novel and interesting",
"strength: Extensive ablation studies and additional results in Appendices",
"strength: I am happy to see, finally, that the transformer based paper discusses and outperforms results on basic baselines, most importantly - Zeng et al. Are transform... | 6.25 |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 34