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Benchmarking the Personalization Capabilities of Large Language Models

arXiv:2607.20471v1 Announce Type: new Abstract: Personalization, the act of varying a message to induce action from a specific receiver while keeping sender, channel, and time fixed, has a long tradit

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Benchmarking Unlearning for Vision Transformers

DGX agent

arXiv:2602.20114v2 Announce Type: replace-cross Abstract: Machine unlearning (MU) refers to the post-training capability to remove (the influence of) training examples that are incorrect, biased, or l

model-releasesarxiv-cs-ai

24 Jul 2026

Best-of-Evidence: Best-of-N Selection under Partial Verification

arXiv:2607.20950v1 Announce Type: new Abstract: BoN improves model outputs by sampling several candidates and selecting one with a proxy score, but it assumes that complete candidates can be evaluated

Applications

Beyond Episodic Evaluation: Memory Architectural Bottlenecks in Sequential Embodied Question Answering

arXiv:2607.21571v1 Announce Type: new Abstract: Embodied question answering (EQA) is traditionally evaluated under an episodic formulation, where agents solve each task independently and reset interna

applicationsarxiv-cs-ro

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models

arXiv:2607.20832v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) remain difficult to detect because only a small fraction of events in large-scale logs are attack-related, and inve

Beyond Independent Optimization: Compression, MoE Routing, and Quantization Interactions in Multimodal Edge Intelligence

arXiv:2607.20981v1 Announce Type: new Abstract: Efficient multimodal inference is increasingly constrained not only by model quality or FLOP count, but also by the cost of preserving, moving, routing,

Beyond Liars' Bench: The Impact of Lie Typology, Depth, and Sparsity on Deception Detection in LLMs

arXiv:2607.20479v1 Announce Type: new Abstract: Training probes to detect deceptive outputs from large language models is still an open problem. Recent work has demonstrated that detection probes fail

Beyond SBDD: Geometric Deep Learning in Polypharmacology and Multi-target Drug Design

arXiv:2607.20550v1 Announce Type: cross Abstract: The traditional 'one drug, one target' paradigm of structure-based drug design (SBDD) frequently proves inadequate for treating multifactorial disease

tutorialsarxiv-cs-ai

Applications

Beyond Sufficiency: Time Series Explanation with Counterfactual Necessity

arXiv:2607.21573v1 Announce Type: cross Abstract: Faithful explanations of time-series classifiers should identify subsequences that are not only sufficient to preserve a black-box model's prediction,

applicationsarxiv-cs-ai

Safety

Beyond Sycophancy: Structured Resistance and Compliance in LLM Moral Reasoning

arXiv:2607.21558v1 Announce Type: new Abstract: Building socially calibrated large language models, which can learn from others without simply yielding to them, requires more than reducing sycophancy

safetyarxiv-cs-ai

Black box behavioural modelling: Predicting human activity schedules with a deep conditional generative approach

arXiv:2512.04223v2 Announce Type: replace Abstract: Modelling the complexity and diversity of human activity scheduling behaviour is inherently challenging. We demonstrate ActVAE, a deep conditional-g

Boltzmann generators for amorphous particle systems

arXiv:2512.16607v2 Announce Type: replace-cross Abstract: Sampling configurations in thermodynamic equilibrium is a long-standing challenge in statistical physics. Boltzmann generators address this pr

Boosting Robustness for All-Weather Self-Supervised Depth Estimation in Autonomous Driving

arXiv:2607.21526v1 Announce Type: new Abstract: Self-supervised depth estimation is challenging for safe autonomous driving under various adverse weather conditions due to sensor perception degradatio

agentsarxiv-cs-cv

Bound-Founded Semantics for Answer Set Programming with Difference Constraints: Preliminary Report

arXiv:2607.21201v1 Announce Type: new Abstract: While the integration of linear constraints has significantly expanded the reach of Answer Set Programming (ASP), existing hybrid solvers often rely on

Break Through the Compression Bottleneck: From Theory to Practice

arXiv:2607.20434v1 Announce Type: cross Abstract: As the parameter size of language models continues to grow, effective model compression is required to reduce their computational and memory overhead.

Bridging the Gap Between Plausibility and Admissibility: Constraint-Aware Flow Maps for Dynamic Graph Systems

arXiv:2607.21421v1 Announce Type: new Abstract: Generative models can support decision-making under uncertainty by producing ensembles of plausible future system trajectories, but statistical plausibi

C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs

arXiv:2607.21076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) require huge memory and computational costs, which limits their practical deployment. Post-training quantizatio

tutorialsarxiv-cs-cv

CAMeR: Keyword-Gated Hybrid Activation for Adaptive Memory Retention in LLM Agents

arXiv:2607.20458v1 Announce Type: cross Abstract: Large language model (LLM) agents operating over extended dialogues accumulate vast amounts of information, yet existing memory systems either retain

Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows

arXiv:2607.17528v3 Announce Type: replace Abstract: Large language model (LLM) agents are extending electronic design automation (EDA) beyond static RTL generation toward long-horizon, tool-interactiv

agentsarxiv-cs-ai

Can an AI System Be Creative? A Critical Perspective from Art and Engineering

arXiv:2607.20796v1 Announce Type: new Abstract: This paper examines the question of whether artificial intelligence (AI) systems can be creative, approached from the dual perspective of a researcher t

Can Generative Recommendation Reach Cold Items? A Temporal Perspective on Semantic-ID Generation

arXiv:2607.21101v1 Announce Type: new Abstract: Semantic-ID-based generative recommendation represents items as sequences of shared semantic tokens, enabling token recombination beyond isolated item I

Can Valence Reflect Morality in Natural Language? A Preliminary Annotation Study

arXiv:2607.20461v1 Announce Type: cross Abstract: Present implementations of artificial intelligence (AI) ethics do not adequately take feelings, or affect, into account. If AI should be aligned with

CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits

arXiv:2607.20518v1 Announce Type: new Abstract: AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchma

Capital Markets LLM Reliability Score (CM-LRS): From Plausible to Bankable

model-releasesarxiv-cs-cl

arXiv:2607.21340v1 Announce Type: new Abstract: In capital-markets workflows the question is rarely whether a large language model can produce a fluent draft, but whether the draft is bankable: defens

Cardinality-Decomposed Loss: Matching Training Objectives to Relation Structure in Heterogeneous Recommendation Graphs

model-releasesarxiv-cs-lg

arXiv:2607.20737v1 Announce Type: new Abstract: Graph Neural Networks trained on heterogenous bipartite graphs form a common basis in recommendation systems. These graphs often express relations that

Local Ai

CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data

arXiv:2607.21088v1 Announce Type: new Abstract: Deep subspace clustering plays a critical role in applications involving multivariate spatiotemporal data, such as sea ice monitoring, disease spread an

local-aiarxiv-cs-lg

Applications

Case study: proving sqrt(2) irrational with LPTP and an LLM

arXiv:2607.21187v1 Announce Type: cross Abstract: We present the interactions with an LLM (Large Language Model) aiming at proving that the square root of 2 is not a rational number in an LP (Logic Pr

applicationsarxiv-cs-ai

Case study: solving P-99 with LPTP and an LLM

arXiv:2607.21196v1 Announce Type: cross Abstract: Ninety-Nine Prolog Problems (P-99) is a famous set of Prolog exercises. We solved the first thirty three just by prompting an LLM (Large Language Mode

Causal-AgentIR: Self-Evolving Causal Memory for Adaptive Image Restoration Agents

arXiv:2607.21125v1 Announce Type: new Abstract: Image restoration agents have recently emerged as a flexible paradigm for handling diverse and unpredictable degradations in real-world scenarios. Exist

agentsarxiv-cs-cv

Cautious optimism for deep parameterized quantum circuits

arXiv:2607.21409v1 Announce Type: cross Abstract: A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it rema

CEDAR: Causal Edge Discovery for Autoregressive Processes

arXiv:2607.20696v1 Announce Type: new Abstract: We propose CEDAR (Causal Edge Discovery for Autoregressive Processes), a constraint-based method for lagged causal edge discovery in sparse autoregressi

Chemical Chain-of-Thought Functions as a Hallucination-Prone Molecular Scratchpad

arXiv:2607.20935v1 Announce Type: cross Abstract: Chemical reasoning language models are expected to derive molecular answers through faithful chain-of-thought (CoT). However, across four reasoning mo

researcharxiv-cs-cl

Chess_db: A framework for working with large chess game datasets

arXiv:2607.21195v1 Announce Type: cross Abstract: Chess is a two player strategic game that is embedded in classical AI culture as it was once the frontier for intelligent behaviour. There was the sil

Chronofy: A Temporal-Logical Decay Architecture for Information Validity in Time-Aware Retrieval-Augmented Generation

model-releasesarxiv-cs-lg

arXiv:2607.20560v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RA

Classifier-pruned Bayesian optimization for particle accelerator tuning: Exploring temporally structured manifold of 6D beam phase space

model-releasesarxiv-cs-lg

arXiv:2412.01748v2 Announce Type: replace Abstract: Complex dynamical systems, such as particle accelerators, often require intricate and time-consuming tuning procedures to achieve optimal performanc

ClickGuard: Detecting and Spoiling Clickbait News with Informativeness Measures and Large Language Models

arXiv:2607.20463v1 Announce Type: new Abstract: This paper presents an AI-driven browser extension that identifies clickbait to help users avoid misleading Internet articles. Moving beyond traditional

Safety

Climate-resilient electric vehicle charging infrastructure for sustainable cities: An interpretable causal-ensemble framework for preventive maintenance and low-carbon mobility

arXiv:2607.21444v1 Announce Type: cross Abstract: Reliable electric vehicle (EV) charging infrastructure is a cornerstone of sustainable, low-carbon cities, yet urban climate stress such as extreme he

safetyarxiv-cs-lg

CLOAK: Contrastive Guidance for Latent Diffusion-Based Data Obfuscation

arXiv:2512.12086v2 Announce Type: replace Abstract: Data obfuscation is a promising technique for mitigating attribute inference attacks by semi-trusted parties with access to time-series data emitted

tutorialsarxiv-cs-lg

CLOE: Christoffel Loss Autoencoder for Anomaly Detection

arXiv:2607.20530v1 Announce Type: cross Abstract: Semi-supervised anomaly detection plays a key role in diverse fields such as process monitoring, healthcare, and finance. However, lightweight methods

tutorialsarxiv-cs-ai

CLUIE: Clustering-Aware Recurrent Propagation with Local Structural Compensation for Underwater Image Enhancement

arXiv:2607.21467v1 Announce Type: new Abstract: Underwater image enhancement remains challenging due to wavelength-dependent light absorption, scattering, and backscattering, which jointly cause color

researcharxiv-cs-cv

Clustered Edge Intelligence: Beyond Just Convergence of Edge Computing and AI

arXiv:2607.20937v1 Announce Type: new Abstract: We are moving from an information age to the age of intelligence. A decade, or possibly less than that, data will not be the gold anymore rather the der

CMI-Mem: Toward Generalizable Long-Term Memory Management via CMI-Augmented Reinforcement Learning

arXiv:2607.20553v1 Announce Type: new Abstract: Memory Manager models are pivotal in agent systems. Existing methods rely predominantly on LLM-judged synthetic question-answer (QA) pairs, making memor

agentsarxiv-cs-ai

Code Monitor Red Teaming for Public-Test-Passing Code

arXiv:2607.20852v1 Announce Type: new Abstract: Visible tests are a common gate for LLM-generated code, but passing them does not certify specification correctness. We study a deployment-like monitori

Codec-Gauge: Learning Compression-Friendly Gauges for Transformer KV Caches

arXiv:2607.20538v1 Announce Type: cross Abstract: Long-context Transformer inference increasingly relies on KV-cache compression or quantization. Prior rotation and transform-coding results suggest th

Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections

arXiv:2607.21488v1 Announce Type: cross Abstract: Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, whi

agentsarxiv-cs-ai

Safety

Compile, Then Page: Executable SOP Programs and a Capability-Gated Runtime for Procedural LLM Agents

arXiv:2607.11346v3 Announce Type: replace Abstract: Enterprise agents must follow long-horizon, conditional, safety-critical standard operating procedures (SOPs). We compile machine-readable SOP const

safetyarxiv-cs-ai

Compiling to recurrent neurons

arXiv:2511.14953v2 Announce Type: replace-cross Abstract: Discrete structures are currently second-class in differentiable programming. Since functions over discrete structures lack overt derivatives,

Local Ai

Concept Concentration for Faithful Representation Intervention

arXiv:2505.18672v2 Announce Type: replace Abstract: Representation intervention aims to localize and modify the representations that encode the underlying concepts in large language models (LLMs) to e

local-aiarxiv-cs-lg