Papers Position
“Position” 태그가 달린 논문 3,684편 · 필터 해제
Large Language Models Can Be a Viable Substitute for Expert Political Surveys When a Shock Disrupts Traditional Measurement Approaches
After a disruptive event or shock, such as the Department of Government Efficiency (DOGE) federal layoffs of 2025, expert judgments are colored by knowledge of the outcome. This can make it difficult or impossible to rec…
PositionCan Theoretical Physics Research Benefit from Language Agents?
Large Language Models (LLMs) are rapidly advancing across diverse domains, yet their application in theoretical physics research is not yet mature. This position paper argues that LLM agents can potentially help accelera…
Code GenerationMathematical ReasoningPhysical IntuitionPosition+1ComRoPE: Scalable and Robust Rotary Position Embedding Parameterized by Trainable Commuting Angle Matrices
The Transformer architecture has revolutionized various regions since it was proposed, and its effectiveness largely depends on the ability to encode positional information. Traditional position encoding methods exhibit …
PositionPOSS: Position Specialist Generates Better Draft for Speculative Decoding
Speculative decoding accelerates Large Language Model (LLM) inference by using a small draft model to predict multiple tokens, and a large target model to verify these tokens in parallel. Recent studies leverage the hidd…
Language ModelingLanguage ModellingLarge Language ModelPositionOcclusion-Aware Ground Target Tracking by a Dubins Vehicle using Visibility Volumes
This paper considers the problem of tracking a point of interest (POI) moving along a known trajectory on the ground with an uncrewed aerial vehicle (UAV) modeled as a Dubins vehicle using a line-of-sight (LOS) sensor th…
PositionEDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment
Deep reinforcement learning agents are often fragile while humans remain adaptive and flexible to varying scenarios. To bridge this gap, we present EDEN, a biologically inspired navigation framework that integrates learn…
Autonomous NavigationDeep Reinforcement LearningPositionreinforcement-learning+1Elasticity of substitution and general model of economic growth
The main purpose of this paper is to generalize some recent results obtained by Chilarescu and Manuel Gomez. Essentially, we are trying to study the effect of elasticity of substitution on the parameters of economic grow…
PositionSmall Language Models are the Future of Agentic AI
Large language models (LLMs) are often praised for exhibiting near-human performance on a wide range of tasks and valued for their ability to hold a general conversation. The rise of agentic AI systems is, however, usher…
AI AgentPositionPosition: Olfaction Standardization is Essential for the Advancement of Embodied Artificial Intelligence
Despite extraordinary progress in artificial intelligence (AI), modern systems remain incomplete representations of human cognition. Vision, audition, and language have received disproportionate attention due to well-def…
EthicsNavigatePositionDetecting Airborne Objects with 5G NR Radars
The integration of sensing capabilities into 5G New Radio (5G NR) networks offers an opportunity to enable the detection of airborne objects without the need for dedicated radars. This paper investigates the feasibility …
Integrated sensing and communicationISACPositionNote on the size of a stable matching
Consider a one-to-one two-sided matching market with workers on one side and single-position firms on the other, and suppose that the largest individually rational matching contains $n$ pairs. We show that the number of …
PositionSTARS-assisted Near-field ISAC: Sensor Deployment and Beamforming Design
A simultaneously transmitting and reflecting surface (STARS) assisted near-field (NF) integrated sensing and communication (ISAC) framework is proposed, where the radio sensors are installed on the STARS to directly cond…
Integrated sensing and communicationISACPositionPosition Dependent Prediction Combination For Intra-Frame Video Coding
Intra-frame prediction in the High Efficiency Video Coding (HEVC) standard can be empirically improved by applying sets of recursive two-dimensional filters to the predicted values. However, this approach does not allow …
PositionPredictionPosition Paper: Metadata Enrichment Model: Integrating Neural Networks and Semantic Knowledge Graphs for Cultural Heritage Applications
The digitization of cultural heritage collections has opened new directions for research, yet the lack of enriched metadata poses a substantial challenge to accessibility, interoperability, and cross-institutional collab…
Knowledge GraphsPositionPosition: Federated Foundation Language Model Post-Training Should Focus on Open-Source Models
Post-training of foundation language models has emerged as a promising research domain in federated learning (FL) with the goal to enable privacy-preserving model improvements and adaptations to user's downstream tasks. …
Federated LearningLanguage ModelingLanguage ModellingPosition+1Position: The Future of Bayesian Prediction Is Prior-Fitted
Training neural networks on randomly generated artificial datasets yields Bayesian models that capture the prior defined by the dataset-generating distribution. Prior-data Fitted Networks (PFNs) are a class of methods de…
Bayesian InferencePositionThe End Of Universal Lifelong Identifiers: Identity Systems For The AI Era
Many identity systems assign a single, static identifier to an individual for life, reused across domains like healthcare, finance, and education. These Universal Lifelong Identifiers (ULIs) underpin critical workflows b…
PositionCultural Evaluations of Vision-Language Models Have a Lot to Learn from Cultural Theory
Modern vision-language models (VLMs) often fail at cultural competency evaluations and benchmarks. Given the diversity of applications built upon VLMs, there is renewed interest in understanding how they encode cultural …
DiversityPositionSeven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentral…
Disaster ResponsePositionPosition: Uncertainty Quantification Needs Reassessment for Large-language Model Agents
Large-language models (LLMs) and chatbot agents are known to provide wrong outputs at times, and it was recently found that this can never be fully prevented. Hence, uncertainty quantification plays a crucial role, aimin…
ChatbotLanguage ModelingLanguage ModellingLarge Language Model+2