ICLR 2024PastLarge language modelsSafety & alignmentPrivacy & security
ICLR 2024 Workshop on Secure and Trustworthy Large Language Models
SeT LLM @ ICLR 2024
- Submission deadline
- Feb 20, 2024, 23:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (72)
Fetched from OpenReview (v2) on 2026-06-10.
A closer look at adversarial suffix learning for Jailbreaking LLMs
An Assessment of Model-on-Model Deception
Are Large Language Models Bayesian? A Martingale Perspective on In-Context Learning
ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs
Assessing Prompt Injection Risks in 200+ Custom GPTs
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
Attacking LLM Watermarks by Exploiting Their Strengths
Attacks on Third-Party APIs of Large Language Models
Backward Chaining Circuits in a Transformer Trained on a Symbolic Reasoning Task
Bayesian reward models for LLM alignment
BEYOND FINE-TUNING: LORA MODULES BOOST NEAR- OOD DETECTION AND LLM SECURITY
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks
Calibrating Language Models With Adaptive Temperature Scaling
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?
Character-level robustness should be revisited
Coercing LLMs to do and reveal (almost) anything
CollabEdit: Towards Non-destructive Collaborative Knowledge Editing
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
DUAW: Data-free Universal Adversarial Watermark against Stable Diffusion Customization
Enhancing and Evaluating Logical Reasoning Abilities of Large Language Models
Explorations of Self-Repair in Language Model
Exploring the Adversarial Capabilities of Large Language Models
Fight Back Against Jailbreaking via Prompt Adversarial Tuning
Group Preference Optimization: Few-Shot Alignment of Large Language Models
GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models
How many Opinions does your LLM have? Improving Uncertainty Estimation in NLG
How Susceptible are Large Language Models to Ideological Manipulation?
I'm not familiar with the name Harry Potter: Prompting Baselines for Unlearning in LLMs
Initial Response Selection for Prompt Jailbreaking using Model Steering
Is Your Jailbreaking Prompt Truly Effective for Large Language Models?
Large Language Model Bias Mitigation from the Perspective of Knowledge Editing
Leveraging Context in Jailbreaking Attacks
LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B
MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks
On Fairness Implications and Evaluations of Low-Rank Adaptation of Large Models
On Prompt-Driven Safeguarding for Large Language Models
On Trojan Signatures in Large Language Models of Code
Open Sesame! Universal Black-Box Jailbreaking of Large Language Models
PANDORA: Detailed LLM Jailbreaking via Collaborated Phishing Agents with Decomposed Reasoning
PETA: PARAMETER-EFFICIENT TROJAN ATTACKS
Preventing Memorized Completions through White-Box Filtering
Privacy-preserving Fine-tuning of Large Language Models through Flatness
Quantitative Certification of Knowledge Comprehension in LLMs
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?
Retrieval Augmented Prompt Optimization
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding
Safer-Instruct: Aligning Language Models with Automated Preference Data
Self-Alignment of Large Language Models via Social Scene Simulation
Self-evaluation and self-prompting to improve the reliability of LLMs
Sequence-Level Certainty Reduces Hallucination In Knowledge-Grounded Dialogue Generation
Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models
Simple Permutations Can Fool LLaMA: Permutation Attack and Defense for Large Language Models
Single-pass detection of jailbreaking input in large language models
Source-Aware Training Enables Knowledge Attribution in Language Models
Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework
Tailoring Self-Rationalizers with Multi-Reward Distillation
The Effect of Model Size on LLM Post-hoc Explainability via LIME
TOFU: A Task of Fictitious Unlearning for LLMs
Toward Robust Unlearning for LLMs
Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control
TrustScore: Reference-Free Evaluation of LLM Response Trustworthiness
Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations
Watermark Stealing in Large Language Models
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
WatME: Towards Lossless Watermarking Through Lexical Redundancy
What's in Your "Safe" Data?: Identifying Benign Data that Breaks Safety
WinoViz: Probing Visual Properties of Objects Under Different States