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Notes on language models
104 notes, page 5 of 5
Grad Detect: Gradient-Based Hallucination Detection in LLMs
The authors present a new method called Grad Detect, which uses the internal gradient structure of Large Language Models (LLMs) during inference to detect hallucinations. This method outperforms confidence-based and…
Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams
This research explores the use of large language models (LLMs) in detecting scam phone calls in Turkish, a low-resource language where such detection is particularly challenging due to limited annotated data and…
Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams
Researchers introduce a new dataset of Turkish phone call conversations to test large language models' ability to detect scams. They find that using corrected or uncorrected transcripts improves results compared to…
Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity
Researchers propose a new method to enhance large language models while maintaining privacy in sensitive scenarios. The method uses a multi-agent framework that sanitizes retrieved content through semantic rewriting…
Exposing the Illusion of Erasure in Knowledge Editing for LLMs
This research paper explores the reliability and mechanisms of Knowledge Editing (KE) in Language Models (LLMs), revealing that edited knowledge is not always fully erased but can continue to surface even across…
GIF: Locally Sound Geometric Information Flow Control for LLMs
Researchers have proposed a new method called Geometric Information Flow (GIF) for controlling information flow in large language models used in agentic systems. GIF uses the model's Jacobian and local output geometry…
GRINQH: Graded Input-based Quantization Hierarchy for Efficient LLM Generation
The paper presents a method called GRINQH (GRaded INput-based Quantization Hierarchy) to accelerate the decoding process of language models during inference, particularly beneficial for edge-computing settings. The…
Memory Contagion: Cross-Temporal Propagation of Evaluator Bias via Agent Memory
The study identifies a new phenomenon called Memory Contagion, where biased evaluators' influence can affect the experiences of language model agents, causing their memories to become biased as well. This bias is…
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