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GPT, Claude, Gemini, and other LLMs

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Llms

[D] How to break free from LLM's chains as a PhD student?

I didn't realize but over a period of one year i have become overreliant on ChatGPT to write code, I am a second year PhD student and don...

Reddit - Machine Learning · 1 min ·
Llms

[R] Reference model free behavioral discovery of AudiBench model organisms via Probe-Mediated Adaptive Auditing

Anthropic's AuditBench - 56 Llama 3.3 70B models with planted hidden behaviors - their best agent detects the behaviros 10-13% of the tim...

Reddit - Machine Learning · 1 min ·
Llms

[P] Dante-2B: I'm training a 2.1B bilingual fully open Italian/English LLM from scratch on 2×H200. Phase 1 done — here's what I've built.

The problem If you work with Italian text and local models, you know the pain. Every open-source LLM out there treats Italian as an after...

Reddit - Machine Learning · 1 min ·

All Content

[2603.04466] Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation
Llms

[2603.04466] Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation

Abstract page for arXiv paper 2603.04466: Act-Observe-Rewrite: Multimodal Coding Agents as In-Context Policy Learners for Robot Manipulation

arXiv - Machine Learning · 3 min ·
[2603.05232] SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity
Llms

[2603.05232] SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity

Abstract page for arXiv paper 2603.05232: SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity

arXiv - Machine Learning · 3 min ·
[2603.04972] Functionality-Oriented LLM Merging on the Fisher--Rao Manifold
Llms

[2603.04972] Functionality-Oriented LLM Merging on the Fisher--Rao Manifold

Abstract page for arXiv paper 2603.04972: Functionality-Oriented LLM Merging on the Fisher--Rao Manifold

arXiv - Machine Learning · 3 min ·
[2603.04956] WaterSIC: information-theoretically (near) optimal linear layer quantization
Llms

[2603.04956] WaterSIC: information-theoretically (near) optimal linear layer quantization

Abstract page for arXiv paper 2603.04956: WaterSIC: information-theoretically (near) optimal linear layer quantization

arXiv - Machine Learning · 3 min ·
[2603.04948] $\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space
Llms

[2603.04948] $\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space

Abstract page for arXiv paper 2603.04948: $\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space

arXiv - Machine Learning · 4 min ·
[2603.04898] U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Intelligent Planning
Llms

[2603.04898] U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Intelligent Planning

Abstract page for arXiv paper 2603.04898: U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Inte...

arXiv - Machine Learning · 3 min ·
[2603.04851] Why Is RLHF Alignment Shallow? A Gradient Analysis
Llms

[2603.04851] Why Is RLHF Alignment Shallow? A Gradient Analysis

Abstract page for arXiv paper 2603.04851: Why Is RLHF Alignment Shallow? A Gradient Analysis

arXiv - Machine Learning · 3 min ·
[2603.04692] Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings
Llms

[2603.04692] Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings

Abstract page for arXiv paper 2603.04692: Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Mod...

arXiv - Machine Learning · 4 min ·
[2603.04606] PDE foundation model-accelerated inverse estimation of system parameters in inertial confinement fusion
Llms

[2603.04606] PDE foundation model-accelerated inverse estimation of system parameters in inertial confinement fusion

Abstract page for arXiv paper 2603.04606: PDE foundation model-accelerated inverse estimation of system parameters in inertial confinemen...

arXiv - Machine Learning · 4 min ·
[2603.04545] An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs
Llms

[2603.04545] An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs

Abstract page for arXiv paper 2603.04545: An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs

arXiv - Machine Learning · 4 min ·
[2603.04478] Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation
Llms

[2603.04478] Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation

Abstract page for arXiv paper 2603.04478: Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teac...

arXiv - Machine Learning · 4 min ·
[2602.07075] LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
Llms

[2602.07075] LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

Abstract page for arXiv paper 2602.07075: LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

arXiv - Machine Learning · 4 min ·
[2601.23236] YuriiFormer: A Suite of Nesterov-Accelerated Transformers
Llms

[2601.23236] YuriiFormer: A Suite of Nesterov-Accelerated Transformers

Abstract page for arXiv paper 2601.23236: YuriiFormer: A Suite of Nesterov-Accelerated Transformers

arXiv - Machine Learning · 3 min ·
[2601.21149] Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement
Llms

[2601.21149] Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement

Abstract page for arXiv paper 2601.21149: Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement

arXiv - Machine Learning · 4 min ·
[2601.16333] Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextually Important Moments
Llms

[2601.16333] Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextually Important Moments

Abstract page for arXiv paper 2601.16333: Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextuall...

arXiv - AI · 4 min ·
[2601.14327] Yuan3.0 Ultra: A Trillion-Parameter Enterprise-Oriented MoE LLM
Llms

[2601.14327] Yuan3.0 Ultra: A Trillion-Parameter Enterprise-Oriented MoE LLM

Abstract page for arXiv paper 2601.14327: Yuan3.0 Ultra: A Trillion-Parameter Enterprise-Oriented MoE LLM

arXiv - Machine Learning · 4 min ·
[2601.11527] "What if she doesn't feel the same?" What Happens When We Ask AI for Relationship Advice
Llms

[2601.11527] "What if she doesn't feel the same?" What Happens When We Ask AI for Relationship Advice

Abstract page for arXiv paper 2601.11527: "What if she doesn't feel the same?" What Happens When We Ask AI for Relationship Advice

arXiv - AI · 3 min ·
[2601.11063] EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaboration
Llms

[2601.11063] EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robot Collaboration

Abstract page for arXiv paper 2601.11063: EmboTeam: Grounding LLM Reasoning into Reactive Behavior Trees via PDDL for Embodied Multi-Robo...

arXiv - Machine Learning · 4 min ·
[2601.08393] Controlled LLM Training on Spectral Sphere
Llms

[2601.08393] Controlled LLM Training on Spectral Sphere

Abstract page for arXiv paper 2601.08393: Controlled LLM Training on Spectral Sphere

arXiv - Machine Learning · 3 min ·
[2601.04548] Identifying Good and Bad Neurons for Task-Level Controllable LLMs
Llms

[2601.04548] Identifying Good and Bad Neurons for Task-Level Controllable LLMs

Abstract page for arXiv paper 2601.04548: Identifying Good and Bad Neurons for Task-Level Controllable LLMs

arXiv - AI · 4 min ·
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