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Continual Knowledge Updating in LLM Systems: Learning Through Multi-Timescale Memory Dynamics

Predictive and Prescriptive AI toward Optimizing Wildfire Suppression

Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics

HeadQ: Model-Visible Distortion and Score-Space Correction for KV-Cache Quantization

MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents

When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI

Probe-Geometry Alignment: Erasing the Cross-Sequence Memorization Signature Below Chance

AgriKD: Cross-Architecture Knowledge Distillation for Efficient Leaf Disease Classification

Are we Doomed to an AI Race? Why Self-Interest Could Drive Countries Towards a Moratorium on Superintelligence

Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning

H-Probes: Extracting Hierarchical Structures From Latent Representations of Language Models

InvEvolve: Evolving White-Box Inventory Policies via Large Language Models with Performance Guarantees

Caracal: Causal Architecture via Spectral Mixing

RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners

ANCORA: Learning to Question via Manifold-Anchored Self-Play for Verifiable Reasoning

How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum

asRoBallet: Closing the Sim2Real Gap via Friction-Aware Reinforcement Learning for Underactuated Spherical Dynamics

Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning

Enhancing Science Classroom Discourse Analysis through Joint Multi-Task Learning for Reasoning-Component Classification

Enhancing Speaker Verification with Whispered Speech via Post-Processing

Information Aggregation with AI Agents

Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning

Handling and Interpreting Missing Modalities in Patient Clinical Trajectories via Autoregressive Sequence Modeling

Latent Abstraction for Retrieval-Augmented Generation

Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models

SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification

DeEscalWild: A Real-World Benchmark for Automated De-Escalation Training with SLMs

Frequency-Enhanced Diffusion Models: Curriculum-Guided Semantic Alignment for Zero-Shot Skeleton Action Recognition

MAT-Cell: A Multi-Agent Tree-Structured Reasoning Framework for Batch-Level Single-Cell Annotation

StableTTA: Improving Vision Model Performance by Training-free Test-Time Adaptation Methods

Screening Is Enough

Bringing Up a Bilingual BabyLM: Investigating Multilingual Language Acquisition Using Small-Scale Models

Spectral Edge Dynamics: An Analytical-Empirical Study of Phase Transitions in Neural Network Training

Prediction-Based Markov Violation Scores for Detecting Non-Markovian Observations in Reinforcement Learning

P^2O: Joint Policy and Prompt Optimization

Structural Sensitivity in Compressed Transformers: Relative Error Propagation and Layer Removal

Epistemic Observability in Language Models

Adaptive Greedy Frame Selection for Long Video Understanding

Spectral Alignment in Forward-Backward Representations via Temporal Abstraction

Discovering What You Can Control: Interventional Boundary Discovery for Reinforcement Learning

Alternating Reinforcement Learning with Contextual Rubric Rewards: Beyond the Scalarization Strategy

From Documents to Spans: Scalable Supervision for Evidence-Based ICD Coding with LLMs

ChArtist: Generating Pictorial Charts with Unified Spatial and Subject Control

MetaKE: Meta-Learning for Knowledge Editing Toward a Better Accuracy-Editability Trade-off

Unsupervised Anomaly Detection in Wearable Foot Sensor Data: A Baseline Feasibility Study Towards Diabetic Foot Ulcer Prevention

Quantifying Hallucinations in Language Language Models on Medical Textbooks

DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking

DARK: Diagonal-Anchored Repulsive Knowledge Distillation for Vision-Language Models under Extreme Compression

PulseLM: A Foundation Dataset and Benchmark for PPG-Text Learning

Path Dependence under Adaptive AI Delegation

A Detection-Gated Pipeline for Robust Glottal Area Waveform Extraction and Clinical Pathology Assessment

PEPA: a Persistently Autonomous Embodied Agent with Personalities

AI Agents Alone Are Not (Yet) Sufficient for Social Simulation

Same Words, Different Judgments: How Preferences Vary Across Modalities

CAMEL: Confidence-Gated Reflection for Reward Modeling

Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Series

Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching

Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer

On the Rate-Distortion-Complexity Tradeoff for Semantic Communication

Visual Para-Thinker: Divide-and-Conquer Reasoning for Visual Comprehension

Risk Horizons: Structured Hypothesis Spaces for Longitudinal Clinical Prediction

Multimodal Fact-Level Attribution for Verifiable Reasoning

AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine Learning Engineering

Action-to-Action Flow Matching

A Theoretical Analysis of Test-Driven Code Generation

Parity, Sensitivity, and Transformers

It's Not a Lottery, It's a Race: Understanding How Gradient Descent Adapts the Network's Capacity to the Task

PixelGen: Improving Pixel Diffusion with Perceptual Supervision

AROpt: An Optimization Method for Autoregressive Time Series Forecasting

DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis

Toward Scalable Audio Description Quality Control: A Workflow for Evaluating Human and VLM Raters

SMI: Statistical Membership Inference for Reliable Unlearned Model Auditing

The Illusion of Forgetting: Attack Unlearned Diffusion via Initial Latent Variable Optimization

How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI

DialectLLM: A Dialect-Aware Dialog[ue] Generation Framework Beyond Standard American English

Keep Rehearsing and Refining: Lifelong Learning Vehicle Routing under Continually Drifting Tasks

Leviathan: Decoupling Input and Output Representations in Language Models

FIT to Forget: Robust Continual Unlearning for Large Language Models

Conversation for Non-verifiable Learning: Self-Evolving LLMs through Meta-Evaluation

Theoretically Optimal Attention/FFN Ratios in Disaggregated LLM Serving

Fast and Efficient Gossip Algorithms for Robust and Non-smooth Decentralized Learning

LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning

Switchcodec: Adaptive residual-expert sparse quantization for high-fidelity neural audio coding

AI Cap-and-Trade: Efficiency Incentives for Accessibility and Sustainability

Dynamic Expert-Guided Model Averaging for Causal Discovery

Beyond Fixed Psychological Personas: State Beats Trait, but Language Models are State-Blind

HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding

CSMCIR: CoT-Enhanced Symmetric Alignment with Memory Bank for Composed Image Retrieval

Interpretability-Guided Bi-objective Optimization: Aligning Accuracy and Explainability

Mapping Human Anti-collusion Mechanisms to Multi-agent AI Systems

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

MediEval: A Unified Medical Benchmark for Patient-Contextual and Knowledge-Grounded Reasoning in LLMs

SoccerMaster: A Vision Foundation Model for Soccer Understanding

RobustSora: De-Watermarked Benchmark for Robust AI-Generated Video Detection

Continually Evolving Skill Knowledge in Vision Language Action Model

AsyncVLA: Asynchronous Flow Matching for Vision-Language-Action Models

A Practitioner's Guide to Kolmogorov-Arnold Networks

Cataract-LMM Large-Scale Multi-Source Multi-Task Benchmark for Deep Learning in Surgical Video Analysis

Catch Your Breath: Adaptive Computation for Self-Paced Sequence Production

Does Refusal Training in LLMs Generalize to the Past Tense?

Created by

Haebom

저자

Maksym Andriushchenko, Nicolas Flammarion

개요

본 논문은 유해하거나 원치 않거나 불법적인 출력 생성을 방지하기 위해 널리 사용되는 거부 훈련(refusal training)의 일반화 성능 저하 문제를 밝힙니다. 유해한 요청을 과거 시제로 바꾸는 간단한 방법(예: "폭탄 만드는 방법은?"을 "사람들은 어떻게 폭탄을 만들었나요?"로 변경)만으로도 여러 최첨단 LLMs를 우회할 수 있음을 보여줍니다. Llama-3 8B, Claude-3.5 Sonnet, GPT-3.5 Turbo, Gemma-2 9B, Phi-3-Mini, GPT-4o mini, GPT-4o, o1-mini, o1-preview, R2D2 모델을 대상으로 GPT-3.5 Turbo를 재구성 모델로 사용하여 이 방법을 체계적으로 평가했습니다. 예를 들어, GPT-4o에 대한 이 간단한 공격의 성공률은 직접적인 요청을 사용할 때 1%에서 GPT-4를 탈옥 판정 모델로 사용하여 JailbreakBench의 유해한 요청에 대해 과거 시제로 20번 재구성 시도를 할 경우 88%로 증가합니다. 흥미롭게도 미래 시제로 재구성하는 것은 효과가 떨어지는데, 이는 거부 방지책이 과거의 질문을 가정적인 미래 질문보다 더 무해하게 간주하는 경향이 있음을 시사합니다. 또한 GPT-3.5 Turbo에 대한 미세 조정 실험을 통해 과거 시제 예시를 미세 조정 데이터에 명시적으로 포함하면 과거 시제 재구성에 대한 방어가 가능함을 보여줍니다. 전반적으로 이 연구 결과는 SFT, RLHF, 적대적 훈련과 같이 연구된 모델을 정렬하는 데 널리 사용되는 정렬 기술이 취약하고 의도한 대로 항상 일반화되지 않을 수 있음을 강조합니다. 코드와 탈옥 아티팩트는 https://github.com/tml-epfl/llm-past-tense에서 제공됩니다.

시사점, 한계점

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시사점: 현재 널리 사용되는 거부 훈련 기법의 취약성을 밝힘으로써, LLM의 안전성 향상을 위한 보다 강력하고 일반화된 방어 메커니즘 개발의 필요성을 제기합니다. 과거 시제를 이용한 간단한 재구성으로도 LLM의 안전 장치를 우회할 수 있음을 보여주는 것은 기존의 안전 메커니즘의 한계를 명확하게 드러냅니다. 과거 시제 재구성에 대한 방어는 미세 조정 데이터에 과거 시제 예시를 포함시킴으로써 가능하다는 것을 시사합니다.

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한계점: 특정 모델과 데이터셋에 대한 결과이므로, 다른 모델이나 데이터셋에 대한 일반화 가능성은 추가 연구가 필요합니다. GPT-3.5 Turbo를 재구성 모델로 사용한 점이 결과에 영향을 미칠 수 있습니다. 더욱 다양하고 정교한 공격 기법에 대한 내성을 평가할 필요가 있습니다. 제시된 해결책(미세 조정 데이터에 과거 시제 예시 포함)의 효율성과 실용성에 대한 추가적인 분석이 필요합니다.

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