· ai
[Paper] Privacy in Federated Learning with Spiking Neural Networks
Spiking neural networks (SNNs) have emerged as prominent candidates for embedded and edge AI. Their inherent low power consumption makes them far more efficient...
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- · software
[Paper] Exploring Hidden Geographic Disparities in Android Apps
While mobile app evolution has been widely studied, geographical variation in app behavior remains largely unexplored. This paper presents a large-scale study o...
- · ai
[Paper] How to Correctly Report LLM-as-a-Judge Evaluations
Large language models (LLMs) are increasingly used as evaluators in lieu of humans. While scalable, their judgments are noisy due to imperfect specificity and s...
- · ai
[Paper] MortgageLLM: Domain-Adaptive Pretraining with Residual Instruction Transfer, Alignment Tuning, and Task-Specific Routing
Large Language Models (LLMs) demonstrate exceptional capabilities across general domains, yet their application to specialized sectors such as mortgage finance ...
- · ai
[Paper] Orthographic Constraint Satisfaction and Human Difficulty Alignment in Large Language Models
Large language models must satisfy hard orthographic constraints during controlled text generation, yet systematic cross-architecture evaluation remains limited...
- · ai
[Paper] Zipf Distributions from Two-Stage Symbolic Processes: Stability Under Stochastic Lexical Filtering
Zipf's law in language lacks a definitive origin, debated across fields. This study explains Zipf-like behavior using geometric mechanisms without linguistic el...
- · ai
[Paper] Semantic Anchors in In-Context Learning: Why Small LLMs Cannot Flip Their Labels
Can in-context learning (ICL) override pre-trained label semantics, or does it merely refine an existing semantic backbone? We address this question by treating...
- · software
[Paper] Lightweight Model Editing for LLMs to Correct Deprecated API Recommendations
Pre-trained or fine-tuned on large code corpora, Large Language Models (LLMs) have demonstrated strong performance in code completion tasks. However, their embe...
- · ai
[Paper] TrackList: Tracing Back Query Linguistic Diversity for Head and Tail Knowledge in Open Large Language Models
Large Language Models (LLMs) have proven efficient in giving definition-type answers to user input queries. While for humans giving various types of answers, su...
- · ai
[Paper] RosettaSpeech: Zero-Shot Speech-to-Speech Translation from Monolingual Data
The scarcity of parallel speech corpora critically hampers speech-to-speech translation (S2ST), often forcing reliance on complex, multi-stage pipelines. This p...
- · ai
[Paper] Towards Audio Token Compression in Large Audio Language Models
Large Audio Language Models (LALMs) demonstrate impressive performance across diverse tasks, ranging from speech recognition to general audio understanding. How...
- · ai
[Paper] TrafficLens: Multi-Camera Traffic Video Analysis Using LLMs
Traffic cameras are essential in urban areas, playing a crucial role in intelligent transportation systems. Multiple cameras at intersections enhance law enforc...