Large Language Models

GPT, Claude, Gemini, and other LLMs

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What is AI, how do apps like ChatGPT work and why are there concerns?
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What is AI, how do apps like ChatGPT work and why are there concerns?

AI is transforming modern life, but some critics worry about its potential misuse and environmental impact.

AI News - General · 7 min ·
[2603.29957] Think Anywhere in Code Generation
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[2603.29957] Think Anywhere in Code Generation

Abstract page for arXiv paper 2603.29957: Think Anywhere in Code Generation

arXiv - Machine Learning · 3 min ·
[2603.16880] NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning
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[2603.16880] NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning

Abstract page for arXiv paper 2603.16880: NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectr...

arXiv - Machine Learning · 4 min ·

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[2603.22629] LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation
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[2603.22629] LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation

Abstract page for arXiv paper 2603.22629: LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation

arXiv - AI · 4 min ·
[2603.22665] Improving LLM Predictions via Inter-Layer Structural Encoders
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[2603.22665] Improving LLM Predictions via Inter-Layer Structural Encoders

Abstract page for arXiv paper 2603.22665: Improving LLM Predictions via Inter-Layer Structural Encoders

arXiv - Machine Learning · 3 min ·
[2603.22623] To Agree or To Be Right? The Grounding-Sycophancy Tradeoff in Medical Vision-Language Models
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[2603.22623] To Agree or To Be Right? The Grounding-Sycophancy Tradeoff in Medical Vision-Language Models

Abstract page for arXiv paper 2603.22623: To Agree or To Be Right? The Grounding-Sycophancy Tradeoff in Medical Vision-Language Models

arXiv - AI · 4 min ·
[2603.22563] Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling
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[2603.22563] Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling

Abstract page for arXiv paper 2603.22563: Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling

arXiv - Machine Learning · 3 min ·
[2603.22499] OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection
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[2603.22499] OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection

Abstract page for arXiv paper 2603.22499: OrgForge-IT: A Verifiable Synthetic Benchmark for LLM-Based Insider Threat Detection

arXiv - Machine Learning · 4 min ·
[2603.22593] Language Models Can Explain Visual Features via Steering
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[2603.22593] Language Models Can Explain Visual Features via Steering

Abstract page for arXiv paper 2603.22593: Language Models Can Explain Visual Features via Steering

arXiv - AI · 3 min ·
[2603.22582] Lie to Me: How Faithful Is Chain-of-Thought Reasoning in Reasoning Models?
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[2603.22582] Lie to Me: How Faithful Is Chain-of-Thought Reasoning in Reasoning Models?

Abstract page for arXiv paper 2603.22582: Lie to Me: How Faithful Is Chain-of-Thought Reasoning in Reasoning Models?

arXiv - AI · 4 min ·
[2603.22577] STRIATUM-CTF: A Protocol-Driven Agentic Framework for General-Purpose CTF Solving
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[2603.22577] STRIATUM-CTF: A Protocol-Driven Agentic Framework for General-Purpose CTF Solving

Abstract page for arXiv paper 2603.22577: STRIATUM-CTF: A Protocol-Driven Agentic Framework for General-Purpose CTF Solving

arXiv - AI · 4 min ·
[2603.22528] GraphRAG for Engineering Diagrams: ChatP&ID Enables LLM Interaction with P&IDs
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[2603.22528] GraphRAG for Engineering Diagrams: ChatP&ID Enables LLM Interaction with P&IDs

Abstract page for arXiv paper 2603.22528: GraphRAG for Engineering Diagrams: ChatP&ID Enables LLM Interaction with P&IDs

arXiv - AI · 4 min ·
[2603.22519] LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface
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[2603.22519] LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface

Abstract page for arXiv paper 2603.22519: LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface

arXiv - AI · 4 min ·
[2603.22510] Do Large Language Models Reduce Research Novelty? Evidence from Information Systems Journals
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[2603.22510] Do Large Language Models Reduce Research Novelty? Evidence from Information Systems Journals

Abstract page for arXiv paper 2603.22510: Do Large Language Models Reduce Research Novelty? Evidence from Information Systems Journals

arXiv - AI · 3 min ·
[2603.22492] Tiny Inference-Time Scaling with Latent Verifiers
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[2603.22492] Tiny Inference-Time Scaling with Latent Verifiers

Abstract page for arXiv paper 2603.22492: Tiny Inference-Time Scaling with Latent Verifiers

arXiv - AI · 4 min ·
[2603.22479] Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games
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[2603.22479] Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games

Abstract page for arXiv paper 2603.22479: Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games

arXiv - AI · 3 min ·
[2603.22473] Functional Component Ablation Reveals Specialization Patterns in Hybrid Language Model Architectures
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[2603.22473] Functional Component Ablation Reveals Specialization Patterns in Hybrid Language Model Architectures

Abstract page for arXiv paper 2603.22473: Functional Component Ablation Reveals Specialization Patterns in Hybrid Language Model Architec...

arXiv - AI · 3 min ·
[2603.22355] Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees
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[2603.22355] Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees

Abstract page for arXiv paper 2603.22355: Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalizat...

arXiv - Machine Learning · 4 min ·
[2603.22344] Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study
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[2603.22344] Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study

Abstract page for arXiv paper 2603.22344: Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study

arXiv - Machine Learning · 4 min ·
[2603.22459] LLM-guided headline rewriting for clickability enhancement without clickbait
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[2603.22459] LLM-guided headline rewriting for clickability enhancement without clickbait

Abstract page for arXiv paper 2603.22459: LLM-guided headline rewriting for clickability enhancement without clickbait

arXiv - AI · 4 min ·
[2603.22446] Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs
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[2603.22446] Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs

Abstract page for arXiv paper 2603.22446: Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs

arXiv - AI · 4 min ·
[2603.22330] Fair splits flip the leaderboard: CHANRG reveals limited generalization in RNA secondary-structure prediction
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[2603.22330] Fair splits flip the leaderboard: CHANRG reveals limited generalization in RNA secondary-structure prediction

Abstract page for arXiv paper 2603.22330: Fair splits flip the leaderboard: CHANRG reveals limited generalization in RNA secondary-struct...

arXiv - Machine Learning · 3 min ·
[2603.22376] AI Co-Scientist for Ranking: Discovering Novel Search Ranking Models alongside LLM-based AI Agents with Cloud Computing Access
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[2603.22376] AI Co-Scientist for Ranking: Discovering Novel Search Ranking Models alongside LLM-based AI Agents with Cloud Computing Access

Abstract page for arXiv paper 2603.22376: AI Co-Scientist for Ranking: Discovering Novel Search Ranking Models alongside LLM-based AI Age...

arXiv - AI · 4 min ·
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