paper string | soundness float64 | overall_assessment float64 | reviews list | filename string |
|---|---|---|---|---|
Double-Checker: Large Language Model as a Checker for Few-shot Named Entity Recognition Abstract Recently, few-shot Named Entity Recognition (NER) has attracted significant attention due to the high cost of obtaining high-quality labeled data. Decomposition-based methods have demonstrated remarkable performance on this... | 3.5 | 3 | [
{
"comments_suggestions_and_typos": "1. It would be helpful if the authors could provide more details on how the LLM is utilized in the two-stage check process. Specifically, how does the LLM differentiate between entities and non-entities?\n2. Including code or pseudocode for the type-adaptive selector and the... | 5341a7d245bf7fb0d57f668787693363afd32e26df6b378c9fe8b5a1ebf80d730d1d811d783ddc431a77f286d9c1caa2c042d5a0f5f3a282a3708253d42d6462.json |
Enhancing Temporal Modeling of Video LLMs via Time Gating Abstract Video Large Language Models (Video LLMs) have achieved impressive performance on video-and-language tasks, such as video ques- tion answering. However, most existing Video LLMs neglect temporal information in video data, leading to struggles with tempor... | 3 | 3 | [
{
"comments_suggestions_and_typos": "See `Weakness`.",
"ethical_concerns": null,
"paper_summary": "This work proposes a Time Gating Module (TG) to enhance Q-former based methods by injecting temporal information into video features.",
"summary_of_strengths": "This method is simple and effective, sho... | 3466a294c40a84bafdcb7b3768b0bf7218acff4498cf941bce6722d3880bffdc12037bc7ebe4bd54bce1b27213e820255e3beac6569cf71e79526cffeefeddac.json |
GPT-4 Jailbreaks Itself with Near-Perfect Success Using Self-Explanation Abstract Jailbreaking research has been valuable for testing and understanding the safety and se- curity issues of large language models (LLMs). In this paper, we introduce Iterative Refine- ment Induced Self-Jailbreak (IRIS), a novel ap- proach t... | 3 | 3 | [
{
"comments_suggestions_and_typos": "As mentioned in the Limitations section, the paper does not evaluate IRIS on open-source models, which may hinder its applicability.",
"ethical_concerns": null,
"paper_summary": "This paper introduces Iterative Refinement Induced Self-Jailbreak (IRIS), a self-jailbre... | f7389bf0aca1377d6bcd01af399ff34d74b5011e95988730382e5b023fca38bce3254004ad27f79140cb7bf1c27b75127097d39d46654f640d55f390e5bbd1c2.json |
Scaling Sentence Embeddings with Large Language Models Abstract Large Language Models (LLMs) have recently gained significant interest due to their impres- sive results in various natural language tasks. However, their application to sentence em- beddings is still under active research. In this work, we introduce Prompt... | 3.5 | 2.75 | [
{
"comments_suggestions_and_typos": "see above",
"ethical_concerns": null,
"paper_summary": "This paper proposes PromptEOL, a method for obtaining sentence embeddings from LLMs. The proposed model uses a prompt template to summarize the entire sentence into a single word, and then uses the vector repres... | 231724b50bebaf587b8a99fc9c96d1f9b1c94a47a1c1c274e3cb16ab378a40a030777984972de6a03bd208a03bcafee02249cf2de4a7fbc3e5c70a8bbebdb3c3.json |
Can Automatic Metrics Assess High-Quality Translations? Abstract Automatic metrics for evaluating translation quality are typically validated by measuring how well they correlate with human assess- ments. However, correlation methods tend to capture only the ability of metrics to differen- tiate between good and bad so... | 4 | 4 | [
{
"comments_suggestions_and_typos": "See the weaknesses section.",
"ethical_concerns": "N/A",
"paper_summary": "This paper systematically studies how automatic machine translation metrics evaluate high-quality and correct translations. It conducts experiments on existing MT datasets and illustrates that... | 712f081a58b85adf9934f3782880a30b3f55e5c9e2f2031cc7666180b26cf52d1ce9e095ced3e21402f90135d0d83cca226608eb7758f72fb13df13b61aedf9a.json |
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