arXiv:2606.06889v1 Announce Type: new Abstract: Biocodicology, the study of biological information preserved in manuscripts, offers new opportunities to examine parchment as both a textual and biological artefact. This study applies non-destructive sampling to isolate and sequence mitochondrial genomes (mtGenomes) from a 14th-century manuscript, Ms. Codex 1629, which contains both single-use and palimpsested folios. We sought […]
An Abstract Architecture for Explainable Autonomy in Hazardous Environments
arXiv:2606.07211v1 Announce Type: cross Abstract: Autonomous robotic systems are being proposed for use in hazardous environments, often to reduce the risks to human workers. In the immediate future, it is likely that human workers will continue to use and direct these autonomous robots, much like other computerised tools but with more sophisticated decision-making. Therefore, one […]
MOSS-Audio Technical Report
arXiv:2606.01802v3 Announce Type: replace-cross Abstract: MOSS-Audio is a unified audio-language model for speech, environmental sound, and music understanding, supporting audio captioning, time-aware question answering, timestamped transcription, and audio-grounded reasoning. MOSS-Audio couples a dedicated audio encoder with a modality adapter and a large language model: the encoder produces 12.5 Hz temporal representations, the adapter projects them […]
Beyond Waypoints: A Trajectory-Centric Waypointing Paradigm for Vision-Language Navigation
arXiv:2606.07244v1 Announce Type: cross Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) requires agents to follow natural-language instructions while navigating in real-world-like environments. Most VLN-CE approach-es adopt a three-stage framework: a waypoint predictor proposes navigable waypoints, and a navigator selects the best waypoint, with a low-level controller executing the movement to it. However, this decoupled paradigm […]
Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition
arXiv:2606.06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper studies automatic Skill construction from heterogeneous interaction evidence, including demonstrations, agent trajectories, tool traces, and execution logs. We argue that trace-to-skill construction is not simple summarization tasks, because traces […]
Acoustic Cue Alignment in Audio Language Models for Speech Emotion Recognition
arXiv:2606.07309v1 Announce Type: cross Abstract: Instruction-following audio language models (ALMs) can be augmented with explicit acoustic cues, yet it remains unclear whether such cues are used in a grounded way when the raw audio is already available. We study this question in speech emotion recognition (SER) by deriving six interpretable acoustic concept tokens from the […]
SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal
arXiv:2606.07351v1 Announce Type: cross Abstract: Classification of sleep stages is one of the most important diagnostic approaches for a variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful tool for examining the association between neurological effects and sleep phases since it correctly identifies sleep-related neurological alterations. During Non-Rapid Eye Movement (NREM) and Rapid […]
A Temporal Spatial Minimax Rate for Smoothly-Varying Distributions in Wasserstein Space
arXiv:2606.07325v1 Announce Type: cross Abstract: We study the minimax rate of estimating a future value $mu_t_n+h$ of a curve $tmapstomu_t$ in the $2$-Wasserstein space $mathcalP_2(mathbbR^d)$ from finitely many noisy snapshots of its past, under an adiabatic bound $|nabla_t^k v|levarepsilon$ on the $k$-th covariant derivative of the velocity field. Our central result is a unified temporal-spatial […]
Declarative Skills for AI Agents in Knowledge-Grounded Tool-Use Workflows
arXiv:2606.06923v1 Announce Type: new Abstract: We study orchestration mechanisms for tool-using AI agents in realistic customer-service workflows over an unstructured knowledge base. We argue that declarative agents — AI agents equipped with natural-language skill files appended to the system prompt — are an effective orchestration paradigm. Concretely, we compare (i) a DeclarativeAgent that reads three […]
Data-Efficient Autoregressive-to-Diffusion Language Models via On-Policy Distillation
arXiv:2606.06712v1 Announce Type: cross Abstract: We study the transformation of autoregressive models (ARLMs) into diffusion language models (DLMs). Rather than pretraining from scratch, prior work replaces the causal attention in ARLMs with bidirectional attention and then trains the resulting model using a DLM objective. However, these approaches incur two distribution shifts. First, transitioning from a […]
ShallowBench: Benchmarking Generative Drug Design Models on Shallow-Pocket Targets
arXiv:2606.06717v1 Announce Type: cross Abstract: While generative AI models have demonstrated remarkable success in structure-based drug design, they predominantly rely on deep binding pockets and struggle to sample effective ligands for challenging low-pocketability targets, such as the historically “undruggable” oncology targets KRAS and MYC. To address this gap, we introduce ShallowBench, a strictly curated benchmark […]
Quantum-Inspired Trace-Augmented Evidence Selection for Reasoning over Structured Hypothesis Spaces
arXiv:2606.06941v1 Announce Type: new Abstract: Large language models (LLMs) now solve a wide range of expert-level exams at or above human level, yet remain brittle on specialised, evidence-intensive domains such as law. On these tasks, errors arise not only from gaps in world knowledge but also from subtle distinctions between pieces of evidence and inconsistent […]