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What field is the article from? | Title: k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis
Abstract: Most examinations of neural networks' learned latent spaces typically employ
dimensionality reduction techniques such as t-SNE or UMAP. While these methods
effectively capture the overall sample distr... | Machine Learning |
What field is the article from? | Title: Coop: Memory is not a Commodity
Abstract: Tensor rematerialization allows the training of deep neural networks (DNNs)
under limited memory budgets by checkpointing the models and recomputing the
evicted tensors as needed. However, the existing tensor rematerialization
techniques overlook the memory system in dee... | Machine Learning |
What field is the article from? | Title: EELBERT: Tiny Models through Dynamic Embeddings
Abstract: We introduce EELBERT, an approach for compression of transformer-based models
(e.g., BERT), with minimal impact on the accuracy of downstream tasks. This is
achieved by replacing the input embedding layer of the model with dynamic, i.e.
on-the-fly, embedd... | Computational Linguistics |
What field is the article from? | Title: A theory for the sparsity emerged in the Forward Forward algorithm
Abstract: This report explores the theory that explains the high sparsity phenomenon
\citep{tosato2023emergent} observed in the forward-forward algorithm
\citep{hinton2022forward}. The two theorems proposed predict the sparsity
changes of a singl... | Machine Learning |
What field is the article from? | Title: Modeling User Viewing Flow using Large Language Models for Article Recommendation
Abstract: This paper proposes the User Viewing Flow Modeling (SINGLE) method for the
article recommendation task, which models the user constant preference and
instant interest from user-clicked articles. Specifically, we employ a ... | Information Retrieval |
What field is the article from? | Title: FinanceBench: A New Benchmark for Financial Question Answering
Abstract: FinanceBench is a first-of-its-kind test suite for evaluating the performance
of LLMs on open book financial question answering (QA). It comprises 10,231
questions about publicly traded companies, with corresponding answers and
evidence str... | Computational Linguistics |
What field is the article from? | Title: Conflict Transformation and Management. From Cognitive Maps to Value Trees
Abstract: Conflict transformation and management are complex decision processes with
extremely high stakes at hand and could greatly benefit from formal approaches
to decision support. For this purpose we develop a general framework about... | Artificial Intelligence |
What field is the article from? | Title: IEKM: A Model Incorporating External Keyword Matrices
Abstract: A customer service platform system with a core text semantic similarity (STS)
task faces two urgent challenges: Firstly, one platform system needs to adapt
to different domains of customers, i.e., different domains adaptation (DDA).
Secondly, it is ... | Artificial Intelligence |
What field is the article from? | Title: Data Management For Large Language Models: A Survey
Abstract: Data plays a fundamental role in the training of Large Language Models
(LLMs). Effective data management, particularly in the formulation of a
well-suited training dataset, holds significance for enhancing model
performance and improving training effi... | Computational Linguistics |
What field is the article from? | Title: Resfusion: Prior Residual Noise embedded Denoising Diffusion Probabilistic Models
Abstract: Recently, Denoising Diffusion Probabilistic Models have been widely used in
image segmentation, by generating segmentation masks conditioned on the input
image. However, previous works can not seamlessly integrate existin... | Computer Vision |
What field is the article from? | Title: AI Alignment: A Comprehensive Survey
Abstract: AI alignment aims to make AI systems behave in line with human intentions and
values. As AI systems grow more capable, the potential large-scale risks
associated with misaligned AI systems become salient. Hundreds of AI experts
and public figures have expressed conc... | Artificial Intelligence |
What field is the article from? | Title: Solving MaxSAT with Matrix Multiplication
Abstract: We propose an incomplete algorithm for Maximum Satisfiability (MaxSAT)
specifically designed to run on neural network accelerators such as GPUs and
TPUs. Given a MaxSAT problem instance in conjunctive normal form, our procedure
constructs a Restricted Boltzmann... | Artificial Intelligence |
What field is the article from? | Title: Foundation Model Assisted Weakly Supervised Semantic Segmentation
Abstract: This work aims to leverage pre-trained foundation models, such as contrastive
language-image pre-training (CLIP) and segment anything model (SAM), to address
weakly supervised semantic segmentation (WSSS) using image-level labels. To
thi... | Computer Vision |
What field is the article from? | Title: Case Repositories: Towards Case-Based Reasoning for AI Alignment
Abstract: Case studies commonly form the pedagogical backbone in law, ethics, and many
other domains that face complex and ambiguous societal questions informed by
human values. Similar complexities and ambiguities arise when we consider how
AI sho... | Artificial Intelligence |
What field is the article from? | Title: Towards Effective Paraphrasing for Information Disguise
Abstract: Information Disguise (ID), a part of computational ethics in Natural Language
Processing (NLP), is concerned with best practices of textual paraphrasing to
prevent the non-consensual use of authors' posts on the Internet. Research on
ID becomes im... | Information Retrieval |
What field is the article from? | Title: Data Valuation and Detections in Federated Learning
Abstract: Federated Learning (FL) enables collaborative model training while preserving
the privacy of raw data. A challenge in this framework is the fair and
efficient valuation of data, which is crucial for incentivizing clients to
contribute high-quality dat... | Machine Learning |
What field is the article from? | Title: CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks
Abstract: Recent efforts in natural language processing (NLP) commonsense reasoning
research have yielded a considerable number of new datasets and benchmarks.
However, most of these datasets formulate commonsense reasoning challenges in
artificial sce... | Computational Linguistics |
What field is the article from? | Title: Hulk: A Universal Knowledge Translator for Human-Centric Tasks
Abstract: Human-centric perception tasks, e.g., human mesh recovery, pedestrian
detection, skeleton-based action recognition, and pose estimation, have wide
industrial applications, such as metaverse and sports analysis. There is a
recent surge to de... | Computer Vision |
What field is the article from? | Title: Negotiating with LLMS: Prompt Hacks, Skill Gaps, and Reasoning Deficits
Abstract: Large language models LLMs like ChatGPT have reached the 100 Mio user barrier
in record time and might increasingly enter all areas of our life leading to a
diverse set of interactions between those Artificial Intelligence models a... | Computational Linguistics |
What field is the article from? | Title: PROMINET: Prototype-based Multi-View Network for Interpretable Email Response Prediction
Abstract: Email is a widely used tool for business communication, and email marketing
has emerged as a cost-effective strategy for enterprises. While previous
studies have examined factors affecting email marketing performan... | Computational Linguistics |
What field is the article from? | Title: Less is more -- the Dispatcher/ Executor principle for multi-task Reinforcement Learning
Abstract: Humans instinctively know how to neglect details when it comes to solve
complex decision making problems in environments with unforeseeable variations.
This abstraction process seems to be a vital property for most... | Machine Learning |
What field is the article from? | Title: On Leakage in Machine Learning Pipelines
Abstract: Machine learning (ML) provides powerful tools for predictive modeling. ML's
popularity stems from the promise of sample-level prediction with applications
across a variety of fields from physics and marketing to healthcare. However,
if not properly implemented a... | Machine Learning |
What field is the article from? | Title: Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference
Abstract: Understanding adaptive human driving behavior, in particular how drivers
manage uncertainty, is of key importance for developing simulated human driver
models that can be used in the evaluation and development of a... | Robotics |
What field is the article from? | Title: Optimization dependent generalization bound for ReLU networks based on sensitivity in the tangent bundle
Abstract: Recent advances in deep learning have given us some very promising results on
the generalization ability of deep neural networks, however literature still
lacks a comprehensive theory explaining why... | Machine Learning |
What field is the article from? | Title: Land use/land cover classification of fused Sentinel-1 and Sentinel-2 imageries using ensembles of Random Forests
Abstract: The study explores the synergistic combination of Synthetic Aperture Radar
(SAR) and Visible-Near Infrared-Short Wave Infrared (VNIR-SWIR) imageries for
land use/land cover (LULC) classific... | Computer Vision |
What field is the article from? | Title: Linear Log-Normal Attention with Unbiased Concentration
Abstract: Transformer models have achieved remarkable results in a wide range of
applications. However, their scalability is hampered by the quadratic time and
memory complexity of the self-attention mechanism concerning the sequence
length. This limitation... | Machine Learning |
What field is the article from? | Title: Localized Symbolic Knowledge Distillation for Visual Commonsense Models
Abstract: Instruction following vision-language (VL) models offer a flexible interface
that supports a broad range of multimodal tasks in a zero-shot fashion.
However, interfaces that operate on full images do not directly enable the user
to... | Artificial Intelligence |
What field is the article from? | Title: CritiqueLLM: Scaling LLM-as-Critic for Effective and Explainable Evaluation of Large Language Model Generation
Abstract: Since the natural language processing (NLP) community started to make large
language models (LLMs), such as GPT-4, act as a critic to evaluate the quality
of generated texts, most of them only... | Computational Linguistics |
What field is the article from? | Title: Data and Approaches for German Text simplification -- towards an Accessibility-enhanced Communication
Abstract: This paper examines the current state-of-the-art of German text
simplification, focusing on parallel and monolingual German corpora. It reviews
neural language models for simplifying German texts and a... | Computational Linguistics |
What field is the article from? | Title: Damage GAN: A Generative Model for Imbalanced Data
Abstract: This study delves into the application of Generative Adversarial Networks
(GANs) within the context of imbalanced datasets. Our primary aim is to enhance
the performance and stability of GANs in such datasets. In pursuit of this
objective, we introduce... | Machine Learning |
What field is the article from? | Title: Improving Intrinsic Exploration by Creating Stationary Objectives
Abstract: Exploration bonuses in reinforcement learning guide long-horizon exploration
by defining custom intrinsic objectives. Several exploration objectives like
count-based bonuses, pseudo-counts, and state-entropy maximization are
non-stationa... | Machine Learning |
What field is the article from? | Title: LongStory: Coherent, Complete and Length Controlled Long story Generation
Abstract: A human author can write any length of story without losing coherence. Also,
they always bring the story to a proper ending, an ability that current
language models lack. In this work, we present the LongStory for coherent,
compl... | Computational Linguistics |
What field is the article from? | Title: Expressive Sign Equivariant Networks for Spectral Geometric Learning
Abstract: Recent work has shown the utility of developing machine learning models that
respect the structure and symmetries of eigenvectors. These works promote sign
invariance, since for any eigenvector v the negation -v is also an eigenvector... | Machine Learning |
What field is the article from? | Title: Bandit-Driven Batch Selection for Robust Learning under Label Noise
Abstract: We introduce a novel approach for batch selection in Stochastic Gradient
Descent (SGD) training, leveraging combinatorial bandit algorithms. Our
methodology focuses on optimizing the learning process in the presence of label
noise, a p... | Machine Learning |
What field is the article from? | Title: FlexModel: A Framework for Interpretability of Distributed Large Language Models
Abstract: With the growth of large language models, now incorporating billions of
parameters, the hardware prerequisites for their training and deployment have
seen a corresponding increase. Although existing tools facilitate model
... | Machine Learning |
What field is the article from? | Title: ALPHA: AnomaLous Physiological Health Assessment Using Large Language Models
Abstract: This study concentrates on evaluating the efficacy of Large Language Models
(LLMs) in healthcare, with a specific focus on their application in personal
anomalous health monitoring. Our research primarily investigates the
capa... | Machine Learning |
What field is the article from? | Title: Assessing Translation capabilities of Large Language Models involving English and Indian Languages
Abstract: Generative Large Language Models (LLMs) have achieved remarkable advancements
in various NLP tasks. In this work, our aim is to explore the multilingual
capabilities of large language models by using mach... | Computational Linguistics |
What field is the article from? | Title: On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving
Abstract: The pursuit of autonomous driving technology hinges on the sophisticated
integration of perception, decision-making, and control systems. Traditional
approaches, both data-driven and rule-based, have been ... | Computer Vision |
What field is the article from? | Title: Detection of news written by the ChatGPT through authorship attribution performed by a Bidirectional LSTM model
Abstract: The large language based-model chatbot ChatGPT gained a lot of popularity
since its launch and has been used in a wide range of situations. This research
centers around a particular situation... | Computational Linguistics |
What field is the article from? | Title: Analisis Eksploratif Dan Augmentasi Data NSL-KDD Menggunakan Deep Generative Adversarial Networks Untuk Meningkatkan Performa Algoritma Extreme Gradient Boosting Dalam Klasifikasi Jenis Serangan Siber
Abstract: This study proposes the implementation of Deep Generative Adversarial
Networks (GANs) for augmenting t... | Cryptography and Security |
What field is the article from? | Title: Scalable AI Generative Content for Vehicular Network Semantic Communication
Abstract: Perceiving vehicles in a driver's blind spot is vital for safe driving. The
detection of potentially dangerous vehicles in these blind spots can benefit
from vehicular network semantic communication technology. However, efficie... | Artificial Intelligence |
What field is the article from? | Title: Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks
Abstract: Graph contrastive learning has shown great promise when labeled data is
scarce, but large unlabeled datasets are available. However, it often does not
take uncertainty estimation into account. We show that a variational Bayesian
ne... | Machine Learning |
What field is the article from? | Title: Interpreting User Requests in the Context of Natural Language Standing Instructions
Abstract: Users of natural language interfaces, generally powered by Large Language
Models (LLMs),often must repeat their preferences each time they make a similar
request. To alleviate this, we propose including some of a user's... | Computational Linguistics |
What field is the article from? | Title: InterVLS: Interactive Model Understanding and Improvement with Vision-Language Surrogates
Abstract: Deep learning models are widely used in critical applications, highlighting
the need for pre-deployment model understanding and improvement. Visual
concept-based methods, while increasingly used for this purpose, ... | Artificial Intelligence |
What field is the article from? | Title: Active Reinforcement Learning for Robust Building Control
Abstract: Reinforcement learning (RL) is a powerful tool for optimal control that has
found great success in Atari games, the game of Go, robotic control, and
building optimization. RL is also very brittle; agents often overfit to their
training environme... | Machine Learning |
What field is the article from? | Title: The Generalization Gap in Offline Reinforcement Learning
Abstract: Despite recent progress in offline learning, these methods are still trained
and tested on the same environment. In this paper, we compare the
generalization abilities of widely used online and offline learning methods
such as online reinforcemen... | Machine Learning |
What field is the article from? | Title: Machine Learning-Enhanced Aircraft Landing Scheduling under Uncertainties
Abstract: This paper addresses aircraft delays, emphasizing their impact on safety and
financial losses. To mitigate these issues, an innovative machine learning
(ML)-enhanced landing scheduling methodology is proposed, aiming to improve
a... | Artificial Intelligence |
What field is the article from? | Title: Make a Donut: Language-Guided Hierarchical EMD-Space Planning for Zero-shot Deformable Object Manipulation
Abstract: Deformable object manipulation stands as one of the most captivating yet
formidable challenges in robotics. While previous techniques have predominantly
relied on learning latent dynamics through ... | Robotics |
What field is the article from? | Title: Training A Multi-stage Deep Classifier with Feedback Signals
Abstract: Multi-Stage Classifier (MSC) - several classifiers working sequentially in an
arranged order and classification decision is partially made at each step - is
widely used in industrial applications for various resource limitation reasons.
The c... | Machine Learning |
What field is the article from? | Title: The Uli Dataset: An Exercise in Experience Led Annotation of oGBV
Abstract: Online gender based violence has grown concomitantly with adoption of the
internet and social media. Its effects are worse in the Global majority where
many users use social media in languages other than English. The scale and
volume of ... | Computational Linguistics |
What field is the article from? | Title: GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation
Abstract: We present MM-Navigator, a GPT-4V-based agent for the smartphone graphical
user interface (GUI) navigation task. MM-Navigator can interact with a
smartphone screen as human users, and determine subsequent actions to f... | Computer Vision |
What field is the article from? | Title: LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms
Abstract: Large Language Models are traditionally finetuned on large instruction
datasets. However recent studies suggest that small, high-quality datasets can
suffice for general purpose instruction following. This lack of consensus
surround... | Machine Learning |
What field is the article from? | Title: Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks
Abstract: Combinatorial optimization finds an optimal solution within a discrete set of
variables and constraints. The field has seen tremendous progress both in
research and industry. With the success of deep learning in the past de... | Machine Learning |
What field is the article from? | Title: Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach
Abstract: Invariant representation learning (IRL) encourages the prediction from
invariant causal features to labels de-confounded from the environments,
advancing the technical roadmap of out-of-distribution (OOD) generalization.
Desp... | Machine Learning |
What field is the article from? | Title: Anytime-Constrained Reinforcement Learning
Abstract: We introduce and study constrained Markov Decision Processes (cMDPs) with
anytime constraints. An anytime constraint requires the agent to never violate
its budget at any point in time, almost surely. Although Markovian policies are
no longer sufficient, we sh... | Machine Learning |
What field is the article from? | Title: Applying Large Language Models and Chain-of-Thought for Automatic Scoring
Abstract: This study investigates the application of large language models (LLMs),
specifically GPT-3.5 and GPT-4, with Chain-of-Though (CoT)in the automatic
scoring of student-written responses to science assessments. We focused on
overco... | Computational Linguistics |
What field is the article from? | Title: APRICOT: Acuity Prediction in Intensive Care Unit (ICU): Predicting Stability, Transitions, and Life-Sustaining Therapies
Abstract: The acuity state of patients in the intensive care unit (ICU) can quickly
change from stable to unstable, sometimes leading to life-threatening
conditions. Early detection of deteri... | Artificial Intelligence |
What field is the article from? | Title: Designing Interpretable ML System to Enhance Trustworthy AI in Healthcare: A Systematic Review of the Last Decade to A Proposed Robust Framework
Abstract: AI-based medical technologies, including wearables, telemedicine, LLMs, and
digital care twins, significantly impact healthcare. Ensuring AI results are
accur... | Artificial Intelligence |
What field is the article from? | Title: Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
Abstract: People are relying on AI agents to assist them with various tasks. The human
must know when to rely on the agent, collaborate with the agent, or ignore its
suggestions. In this work, we propose to learn rules, grounded in data r... | Machine Learning |
What field is the article from? | Title: OffMix-3L: A Novel Code-Mixed Dataset in Bangla-English-Hindi for Offensive Language Identification
Abstract: Code-mixing is a well-studied linguistic phenomenon when two or more
languages are mixed in text or speech. Several works have been conducted on
building datasets and performing downstream NLP tasks on c... | Computational Linguistics |
What field is the article from? | Title: Characterizing Mechanisms for Factual Recall in Language Models
Abstract: Language Models (LMs) often must integrate facts they memorized in
pretraining with new information that appears in a given context. These two
sources can disagree, causing competition within the model, and it is unclear
how an LM will res... | Computational Linguistics |
What field is the article from? | Title: CovarNav: Machine Unlearning via Model Inversion and Covariance Navigation
Abstract: The rapid progress of AI, combined with its unprecedented public adoption and
the propensity of large neural networks to memorize training data, has given
rise to significant data privacy concerns. To address these concerns, mac... | Machine Learning |
What field is the article from? | Title: Exploring the Limits of ChatGPT in Software Security Applications
Abstract: Large language models (LLMs) have undergone rapid evolution and achieved
remarkable results in recent times. OpenAI's ChatGPT, backed by GPT-3.5 or
GPT-4, has gained instant popularity due to its strong capability across a wide
range of ... | Cryptography and Security |
What field is the article from? | Title: Towards a fuller understanding of neurons with Clustered Compositional Explanations
Abstract: Compositional Explanations is a method for identifying logical formulas of
concepts that approximate the neurons' behavior. However, these explanations
are linked to the small spectrum of neuron activations (i.e., the h... | Machine Learning |
What field is the article from? | Title: Pedestrian and Passenger Interaction with Autonomous Vehicles: Field Study in a Crosswalk Scenario
Abstract: This study presents the outcomes of empirical investigations pertaining to
human-vehicle interactions involving an autonomous vehicle equipped with both
internal and external Human Machine Interfaces (HMI... | Human-Computer Interaction |
What field is the article from? | Title: Leveraging Large Language Models for Collective Decision-Making
Abstract: In various work contexts, such as meeting scheduling, collaborating, and
project planning, collective decision-making is essential but often challenging
due to diverse individual preferences, varying work focuses, and power dynamics
among ... | Computational Linguistics |
What field is the article from? | Title: The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change
Abstract: We present the DURel tool that implements the annotation of semantic
proximity between uses of words into an online, open source interface. The tool
supports standardized human annot... | Computational Linguistics |
What field is the article from? | Title: GSQA: An End-to-End Model for Generative Spoken Question Answering
Abstract: In recent advancements in spoken question answering (QA), end-to-end models
have made significant strides. However, previous research has primarily focused
on extractive span selection. While this extractive-based approach is effective
... | Computational Linguistics |
What field is the article from? | Title: A Foundational Multimodal Vision Language AI Assistant for Human Pathology
Abstract: The field of computational pathology has witnessed remarkable progress in the
development of both task-specific predictive models and task-agnostic
self-supervised vision encoders. However, despite the explosive growth of
genera... | Computer Vision |
What field is the article from? | Title: Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks
Abstract: Learning curve extrapolation aims to predict model performance in later
epochs of training, based on the performance in earlier epochs. In this work,
we argue that, while the inherent uncertainty in the extrapolation of le... | Machine Learning |
What field is the article from? | Title: Privacy Measurement in Tabular Synthetic Data: State of the Art and Future Research Directions
Abstract: Synthetic data (SD) have garnered attention as a privacy enhancing
technology. Unfortunately, there is no standard for quantifying their degree of
privacy protection. In this paper, we discuss proposed quanti... | Artificial Intelligence |
What field is the article from? | Title: Brain-inspired Computing Based on Machine Learning And Deep Learning:A Review
Abstract: The continuous development of artificial intelligence has a profound impact
on biomedical research and other fields.Brain-inspired computing is an
important intersection of multimodal technology and biomedical field. This
pap... | Artificial Intelligence |
What field is the article from? | Title: Post Turing: Mapping the landscape of LLM Evaluation
Abstract: In the rapidly evolving landscape of Large Language Models (LLMs),
introduction of well-defined and standardized evaluation methodologies remains
a crucial challenge. This paper traces the historical trajectory of LLM
evaluations, from the foundation... | Computational Linguistics |
What field is the article from? | Title: Paloma: A Benchmark for Evaluating Language Model Fit
Abstract: Language models (LMs) commonly report perplexity on monolithic data held out
from training. Implicitly or explicitly, this data is composed of
domains$\unicode{x2013}$varying distributions of language. Rather than assuming
perplexity on one distribu... | Computational Linguistics |
What field is the article from? | Title: Sports Recommender Systems: Overview and Research Issues
Abstract: Sports recommender systems receive an increasing attention due to their
potential of fostering healthy living, improving personal well-being, and
increasing performances in sport. These systems support people in sports, for
example, by the recomm... | Information Retrieval |
What field is the article from? | Title: Unscrambling the Rectification of Adversarial Attacks Transferability across Computer Networks
Abstract: Convolutional neural networks (CNNs) models play a vital role in achieving
state-of-the-art performances in various technological fields. CNNs are not
limited to Natural Language Processing (NLP) or Computer ... | Cryptography and Security |
What field is the article from? | Title: Multimodal Group Emotion Recognition In-the-wild Using Privacy-Compliant Features
Abstract: This paper explores privacy-compliant group-level emotion recognition
''in-the-wild'' within the EmotiW Challenge 2023. Group-level emotion
recognition can be useful in many fields including social robotics,
conversationa... | Artificial Intelligence |
What field is the article from? | Title: XAI meets Biology: A Comprehensive Review of Explainable AI in Bioinformatics Applications
Abstract: Artificial intelligence (AI), particularly machine learning and deep learning
models, has significantly impacted bioinformatics research by offering powerful
tools for analyzing complex biological data. However, ... | Artificial Intelligence |
What field is the article from? | Title: Automatic Engineering of Long Prompts
Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in
solving complex open-domain tasks, guided by comprehensive instructions and
demonstrations provided in the form of prompts. However, these prompts can be
lengthy, often comprising hundreds of... | Artificial Intelligence |
What field is the article from? | Title: LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
Abstract: We present LaMPilot, a novel framework for planning in the field of
autonomous driving, rethinking the task as a code-generation process that
leverages established behavioral primitives. This approach aims to addres... | Computational Linguistics |
What field is the article from? | Title: Hierarchical Reinforcement Learning for Power Network Topology Control
Abstract: Learning in high-dimensional action spaces is a key challenge in applying
reinforcement learning (RL) to real-world systems. In this paper, we study the
possibility of controlling power networks using RL methods. Power networks are
... | Machine Learning |
What field is the article from? | Title: RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine
Abstract: Traditional Chinese medicine (TCM) prescription is the most critical form of
TCM treatment, and uncovering the complex nonlinear relationship between
symptoms and TCM is of great significance for clini... | Computational Linguistics |
What field is the article from? | Title: Sample based Explanations via Generalized Representers
Abstract: We propose a general class of sample based explanations of machine learning
models, which we term generalized representers. To measure the effect of a
training sample on a model's test prediction, generalized representers use two
components: a glob... | Machine Learning |
What field is the article from? | Title: MMICT: Boosting Multi-Modal Fine-Tuning with In-Context Examples
Abstract: Although In-Context Learning (ICL) brings remarkable performance gains to
Large Language Models (LLMs), the improvements remain lower than fine-tuning on
downstream tasks. This paper introduces Multi-Modal In-Context Tuning (MMICT),
a nov... | Artificial Intelligence |
What field is the article from? | Title: Can ChatGPT Play the Role of a Teaching Assistant in an Introductory Programming Course?
Abstract: The emergence of Large language models (LLMs) is expected to have a major
impact on education. This paper explores the potential of using ChatGPT, an
LLM, as a virtual Teaching Assistant (TA) in an Introductory Pro... | Human-Computer Interaction |
What field is the article from? | Title: Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
Abstract: Code provides a general syntactic structure to build complex programs and
perform precise computations when paired with a code interpreter - we
hypothesize that language models (LMs) can leverage code-writing to improve
Chain of Tho... | Computational Linguistics |
What field is the article from? | Title: Efficiently Programming Large Language Models using SGLang
Abstract: Large language models (LLMs) are increasingly used for complex tasks
requiring multiple chained generation calls, advanced prompting techniques,
control flow, and interaction with external environments. However, efficient
systems for programmin... | Artificial Intelligence |
What field is the article from? | Title: Offloading and Quality Control for AI Generated Content Services in Edge Computing Networks
Abstract: AI-Generated Content (AIGC), as a novel manner of providing Metaverse
services in the forthcoming Internet paradigm, can resolve the obstacles of
immersion requirements. Concurrently, edge computing, as an evolu... | Artificial Intelligence |
What field is the article from? | Title: KOALA: Self-Attention Matters in Knowledge Distillation of Latent Diffusion Models for Memory-Efficient and Fast Image Synthesis
Abstract: Stable diffusion is the mainstay of the text-to-image (T2I) synthesis in the
community due to its generation performance and open-source nature. Recently,
Stable Diffusion XL... | Computer Vision |
What field is the article from? | Title: Aligning with Whom? Large Language Models Have Gender and Racial Biases in Subjective NLP Tasks
Abstract: Human perception of language depends on personal backgrounds like gender and
ethnicity. While existing studies have shown that large language models (LLMs)
hold values that are closer to certain societal gro... | Computational Linguistics |
What field is the article from? | Title: Web News Timeline Generation with Extended Task Prompting
Abstract: The creation of news timeline is essential for a comprehensive and contextual
understanding of events as they unfold over time. This approach aids in
discerning patterns and trends that might be obscured when news is viewed in
isolation. By orga... | Artificial Intelligence |
What field is the article from? | Title: DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models
Abstract: Nature evolves creatures with a high complexity of morphological and
behavioral intelligence, meanwhile computational methods lag in approaching
that diversity and efficacy. Co-optimization of artificial creatures'
morp... | Robotics |
What field is the article from? | Title: In Search of Lost Online Test-time Adaptation: A Survey
Abstract: In this paper, we present a comprehensive survey on online test-time
adaptation (OTTA), a paradigm focused on adapting machine learning models to
novel data distributions upon batch arrival. Despite the proliferation of OTTA
methods recently, the ... | Artificial Intelligence |
What field is the article from? | Title: Improving Faithfulness for Vision Transformers
Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance for
various vision tasks. One reason behind the success lies in their ability to
provide plausible innate explanations for the behavior of neural architectures.
However, ViTs suffer from... | Computer Vision |
What field is the article from? | Title: 4M: Massively Multimodal Masked Modeling
Abstract: Current machine learning models for vision are often highly specialized and
limited to a single modality and task. In contrast, recent large language
models exhibit a wide range of capabilities, hinting at a possibility for
similarly versatile models in computer... | Computer Vision |
What field is the article from? | Title: Adaptive Image Registration: A Hybrid Approach Integrating Deep Learning and Optimization Functions for Enhanced Precision
Abstract: Image registration has traditionally been done using two distinct approaches:
learning based methods, relying on robust deep neural networks, and
optimization-based methods, applyi... | Computer Vision |
What field is the article from? | Title: A Social-aware Gaussian Pre-trained Model for Effective Cold-start Recommendation
Abstract: The use of pre-training is an emerging technique to enhance a neural model's
performance, which has been shown to be effective for many neural language
models such as BERT. This technique has also been used to enhance the... | Information Retrieval |
What field is the article from? | Title: Teaching Specific Scientific Knowledge into Large Language Models through Additional Training
Abstract: Through additional training, we explore embedding specialized scientific
knowledge into the Llama 2 Large Language Model (LLM). Key findings reveal that
effective knowledge integration requires reading texts f... | Computational Linguistics |
What field is the article from? | Title: Combinatorial Optimization with Policy Adaptation using Latent Space Search
Abstract: Combinatorial Optimization underpins many real-world applications and yet,
designing performant algorithms to solve these complex, typically NP-hard,
problems remains a significant research challenge. Reinforcement Learning (RL... | Machine Learning |
What field is the article from? | Title: ConvD: Attention Enhanced Dynamic Convolutional Embeddings for Knowledge Graph Completion
Abstract: Knowledge graphs generally suffer from incompleteness, which can be
alleviated by completing the missing information. Deep knowledge convolutional
embedding models based on neural networks are currently popular me... | Computational Linguistics |
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