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Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?

HPFA: Hypergraph-Based Paired Failure Attribution for LLM Reasoning

Scaling Textual Gradients via Sampling-Based Momentum

A momentum-based, sampling-driven method for scaling textual gradient optimization in LLM prompt engineering, improving performance and efficiency across diverse NLP tasks.

LLMs Can Get "Brain Rot"!

We find that LLMs can get Brain Rot just like human after browsing enormous brainless social media.

AD-VF: LLM-Automatic Differentiation Enables Fine-Tuning-Free Robot Planning from Formal Methods Feedback

A framework leveraging formal verification feedback for scalable and interpretable LLM-driven robot planning.

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning

A training-free method that robustifies LLM safety alignment against fine-tuning by extrapolating low-rank safety subspaces, significantly reducing attack success rates while preserving model utility.

More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment

A study revealing safety-specific pitfalls of multi-model synthetic preference data in DPO alignment.

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning

The first automated guardrail for agents.

SEAL: Steerable Reasoning Calibration of Large Language Models for Free

A training-free approach that calibrates chain-of-thought reasoning in LLMs, improving accuracy while reducing computational overhead.

MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models

Benchmark for medical hallucination by LLMs.