· 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...
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- · 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] Context-Aware Pragmatic Metacognitive Prompting for Sarcasm Detection
Detecting sarcasm remains a challenging task in the areas of Natural Language Processing (NLP) despite recent advances in neural network approaches. Currently, ...
- · 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...
- · 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...
- · ai
[Paper] QiMeng-Kernel: Macro-Thinking Micro-Coding Paradigm for LLM-Based High-Performance GPU Kernel Generation
Developing high-performance GPU kernels is critical for AI and scientific computing, but remains challenging due to its reliance on expert crafting and poor por...