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Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning

Yong Liu, Zirui Zhu, Chaoyu Gong, Minhao Cheng, Cho-Jui Hsieh, Yang You · Feb 24, 2024

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 75% Moderate protocol signal Freshness: Cold Status: Ready
Automatic Metrics Coding
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper
QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources

Zhikai Li, Xiaoxuan Liu, Banghua Zhu, Zhen Dong, Qingyi Gu, Kurt Keutzer · Oct 11, 2023

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 71% Sparse protocol signal Freshness: Cold Status: Ready
General
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper
MindSet: Vision. A toolbox for testing DNNs on key psychological experiments

Valerio Biscione, Milton L. Montero, Marin Dujmovic, Gaurav Malhotra, Dong Yin, Guillermo Puebla · Apr 8, 2024

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 68% Sparse protocol signal Freshness: Cold Status: Ready
Coding
  • Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision.
  • In almost all cases these benchmarks are observational in the sense they are composed of behavioural and brain responses to naturalistic images that have not been manipulated to test hypotheses regarding how DNNs or humans perceive and…
Open paper
CADGL: Context-Aware Deep Graph Learning for Predicting Drug-Drug Interactions

Azmine Toushik Wasi, Taki Hasan Rafi, Raima Islam, Serbetar Karlo, Dong-Kyu Chae · Mar 25, 2024

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 68% Sparse protocol signal Freshness: Cold Status: Ready
Medicine
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper
A Survey of Large Language Models

Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou · Mar 31, 2023

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 68% Sparse protocol signal Freshness: Cold Status: Ready
General
  • Language is essentially a complex, intricate system of human expressions governed by grammatical rules.
  • In particular, we focus on four major aspects of LLMs, namely pre-training, adaptation tuning, utilization, and capacity evaluation.
Open paper
Multi-agent deep reinforcement learning with centralized training and decentralized execution for transportation infrastructure management

M. Saifullah, K. G. Papakonstantinou, A. Bhattacharya, S. M. Stoffels, C. P. Andriotis · Jan 23, 2024

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 75% Moderate protocol signal Freshness: Cold Status: Fallback
Simulation Env Multi Agent Math
  • To tackle the high dimensionality of state and action spaces, we propose DDMAC-CTDE, a Deep Decentralized Multi-Agent Actor-Critic (DDMAC) reinforcement learning architecture with Centralized Training and Decentralized Execution (CTDE).
  • To demonstrate the utility of the proposed framework, we also develop a new comprehensive benchmark environment representing an existing transportation network in Virginia, U.S., with heterogeneous pavement and bridge assets undergoing nons
Open paper
J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modeling

Wataru Nakata, Kentaro Seki, Hitomi Yanaka, Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari · Jul 22, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 26% Sparse protocol signal Freshness: Cold Status: Ready
General
  • Spoken dialogue is essential for human-AI interactions, providing expressive capabilities beyond text.
  • By providing a robust foundation for training advanced dialogue models, we anticipate that J-CHAT will drive progress in human-AI dialogue research and applications.
Open paper
Demystifying Chains, Trees, and Graphs of Thoughts

Maciej Besta, Florim Memedi, Zhenyu Zhang, Robert Gerstenberger, Guangyuan Piao, Nils Blach · Jan 25, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 26% Sparse protocol signal Freshness: Cold Status: Ready
Math
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper
Community-Informed AI Models for Police Accountability

Benjamin A. T. Grahama, Lauren Brown, Georgios Chochlakis, Morteza Dehghani, Raquel Delerme, Brittany Friedman · Jan 24, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 26% Sparse protocol signal Freshness: Cold Status: Fallback
Pairwise Preference General
  • However, for AI to serve democratic governance effectively, models must be designed to include the preferences and perspectives of the governed.
Open paper
Paraphrase Types Elicit Prompt Engineering Capabilities

Jan Philip Wahle, Terry Ruas, Yang Xu, Bela Gipp · Jun 28, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 23% Sparse protocol signal Freshness: Cold Status: Ready
General
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper
Computational lexical analysis of Flamenco genres

Pablo Rosillo-Rodes, Maxi San Miguel, David Sanchez · May 9, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 23% Sparse protocol signal Freshness: Cold Status: Ready
General
  • Flamenco, recognized by UNESCO as part of the Intangible Cultural Heritage of Humanity, is a profound expression of cultural identity rooted in Andalusia, Spain.
Open paper
Modelling Language using Large Language Models

Jumbly Grindrod · Apr 15, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 23% Sparse protocol signal Freshness: Cold Status: Ready
General
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper
A Review of Deep Learning Methods for Photoplethysmography Data

Guangkun Nie, Jiabao Zhu, Gongzheng Tang, Deyun Zhang, Shijia Geng, Qinghao Zhao · Jan 23, 2024

Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 23% Sparse protocol signal Freshness: Cold Status: Ready
Medicine
  • Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
Open paper

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