arXiv Machine Learning
Jun 15
Curvature-Guided Geometric Representation for Protein-Ligand Binding Affinity Prediction
arXiv:2606. 14159v1 Announce Type: new Abstract: Protein-ligand binding affinity (PLA) prediction is critical in drug discovery.
AI safety and alignment
Alignment, interpretability, red-teaming, bias and privacy: the research on what these systems do when they misbehave.
arXiv Machine Learning
Jun 15
From Uncertain Judgments to Calibrated Rankings: Conformal Elo Estimation for LLM Evaluation
arXiv:2606. 13221v2 Announce Type: replace Abstract: Evaluating new large language models typically requires costly human annotation campaigns at scale.
arXiv AI
Jun 15
Adversarial Concept Search: Predicting Compositional Errors From Feature Geometry
arXiv:2606. 13934v1 Announce Type: new Abstract: Humans cannot always intuit what scenarios are most challenging to LLMs.
arXiv AI
Jun 15
FreoStream:Enhancing Stream Guardrails via Future-Aware Reasoning and Safety-Aligned Optimization
arXiv:2606. 13737v1 Announce Type: cross Abstract: Stream guardrails enable token-level safety detection before full responses are generated.
arXiv Machine Learning
Jun 15
LapidaryEngine: Fully Conversational Crystal Generation
arXiv:2606. 14215v1 Announce Type: new Abstract: The emergence of Large Language Models (LLMs) has inspired the vision of generating bespoke crystal materials directly from natural-language instructions, enabling users to design materials through intuitive, conversational interaction.
arXiv AI
Jun 15
ChronoID: Infusing Explicit Temporal Signals into Semantic IDs for Generative Recommendation
arXiv:2606. 14260v1 Announce Type: cross Abstract: Semantic IDs are crucial in generative recommendation, but with a fundamental limitation: temporal information is not well incorporated into semantic IDs.
arXiv AI
Jun 15
MirrorCheck: Efficient Adversarial Defense for Vision-Language Models
arXiv:2406. 09250v5 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly susceptible to sophisticated adversarial attacks, including adaptive strategies specifically designed to bypass existing defenses.
arXiv Machine Learning
Jun 15
A Low-Rank Subspace Analysis of LLM Interventions
arXiv:2606. 14388v1 Announce Type: new Abstract: Interventions designed to modify a particular behavior in LLMs, such as refusal or sycophancy, often produce unintended changes in other behaviors.
arXiv Machine Learning
Jun 15
Mitigating Heterogeneity-Induced Drift in Hierarchical Sign-Based Federated Learning
arXiv:2602. 02355v2 Announce Type: replace-cross Abstract: Hierarchical federated learning (HFL) is well suited for large-scale wireless and Internet of Things systems, where devices communicate with nearby edge servers before reaching the cloud.
arXiv AI
Jun 15
A Virtuous AI is an Existential Risk
arXiv:2606. 13739v1 Announce Type: cross Abstract: This paper examines trade-offs between AI safety and well-being relative to (i) one of the most promising methods for finetuning super-capable AIs, 'Constitutional AI', and (ii) one of the most influential approaches to understanding complex ethical decision making and the conditions for the well-being of rational agents, 'Virtue Ethics'.
arXiv AI
Jun 15
An Agentic Retrieval Framework for Autonomous Context-Aware Data Quality Assessment
arXiv:2606. 13692v1 Announce Type: cross Abstract: Data quality assessment is a critical prerequisite for effective data analytics and data-driven decision-making, yet it remains a challenging task due to the inherently context-dependent nature of data quality.
arXiv AI
Jun 15
Actionable Interpretability Must Be Defined in Terms of Symmetries
arXiv:2601. 12913v4 Announce Type: replace Abstract: This paper argues that interpretability research in Artificial Intelligence (AI) is fundamentally ill-posed as existing definitions of interpretability fail to describe how interpretability can be formally tested or designed for.
Hugging Face Trending Papers
Jun 15
Auditing Machine Unlearning: A Systematic Research on Whether Models Truly Forget
Machine unlearning has been extensively studied in response to growing privacy concerns and regulatory requirements. However, auditing whether unlearning algorithms have truly erased the influence of specific data remains an open challenge.
Hugging Face Trending Papers
Jun 14
Mitigating Visual Hallucinations in Multimodal Systems through Retrieval-Augmented Reliability-Aware Inference
Multimodal large language models (MLLMs) have demonstrated strong capabilities in vision-language understanding and natural-language response generation. However, these systems can still produce overconfident predictions and hallucination-like outputs, particularly when the visual evidence is weak, ambiguous, or semantically inconsistent.
Hugging Face Trending Papers
Jun 13
Defending against Adaptive Prompt Injection Attacks via Reasoning-enabled Task Alignment
Indirect prompt injection attacks hijack LLM-based agents by embedding malicious instructions in third-party data that the agent retrieves during task execution. Existing defenses report near-zero attack success rate on static benchmarks, yet recent adaptive evaluations show that these results collapse once the attacker is allowed to optimize against the deployed defense.
Hugging Face Trending Papers
Jun 13
Repeated Bilateral Trade: The Quest for Fairness
We study repeated bilateral trade from a fairness perspective. At each round, a fresh seller-buyer pair arrives, and the platform posts a price before observing the traders' valuations.
Hugging Face Trending Papers
Jun 13
Teacher-Student Structure for Domain Adaptation in Ensemble Audio-Visual Video Deepfake Detection
The rapid advancement of generative AI models is leading to more realistic deepfake media, encompassing the manipulation of audio, video, or both. This raises severe privacy and societal concerns.
Towards Data Science
Jun 12
Is Language Visual? An Experiment with Chinese Characters
A story about a broken printer, visual inductive bias, and why the race endedin a tie. The post Is Language Visual?
arXiv AI
Jun 12
NTS-CoT: Mitigating Hallucinations in LLM-based News Timeline Summarization with Chain-of-Thought Reasoning
arXiv:2606. 13171v1 Announce Type: cross Abstract: The rapid updates of online news make tracking event developments challenging, highlighting the need for timeline summarization (TLS).
arXiv AI
Jun 12
Emerging Flexible Designs for Geospatial Multimodal Foundation Models
arXiv:2606. 12595v1 Announce Type: cross Abstract: Foundation models are rapidly transforming Earth observation by enabling scalable pretraining across diverse unlabeled geospatial modalities.