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Dastawez Jahan-Numa

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1353 stories

Public health and medicine worldwide — sourced from WHO News.

Dastawez Jahan-Numa

Heard but Not Heeded: Paralinguistic Information Encoding and Loss in Audio-Language Models

arXiv:2609.00727v1 Announce Type: new Abstract: Audio language models are designed to understand speech, yet it remains unclear whether they capture how something is said beyond what is said. We present a mechanistic ana…

arXiv (cs)1h ago
Dastawez Jahan-Numa

SOVER: Formal Certification of Optimization Reformulations via LLM-Assisted SMT Verification

arXiv:2609.00728v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown remarkable promise in translating and reformulating complex mathematical optimization problems across modeling languages. However, v…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Design and Implementation of a Kalman Filter-Infused Algorithm for Tilt Estimation

arXiv:2609.00730v1 Announce Type: new Abstract: Accurate tilt angle estimation is important in many engineering applications, such as robotics, motion tracking, and embedded control systems. However, measurements from lo…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Agentic Empirical Asset Pricing: Methodological Foundations

arXiv:2609.00731v1 Announce Type: new Abstract: Recent advances in LLM agents enable a new paradigm for asset pricing, which we call Agentic Empirical Asset Pricing (AEAP): systems that autonomously conduct the scientifi…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Inverse Rig Optimization from Line Drawings

arXiv:2609.00732v1 Announce Type: new Abstract: Stylized 3D character animation is largely hand-authored, with animators authoring rig parameters one keyframe at a time to find the best pose. Because stylized work reads …

arXiv (cs)1h ago
Dastawez Jahan-Numa

Online Self-Weighted Fine-Tuning

arXiv:2609.00734v1 Announce Type: new Abstract: Standard supervised fine-tuning (SFT) assigns the same explicit loss weight to every expert demonstration, regardless of the model's changing competence over training queri…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Escaping Redundant Reasoning: Structure-Aware Search for Inference-Time LLMs

arXiv:2609.00738v1 Announce Type: new Abstract: Inference-time search with large language models (LLMs) often concentrates on a small set of structurally or semantically similar trajectories, leaving alternatives underex…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Mind the Rift: Cross-Scale Coupling Mismatch for AI-Generated Video Detection

arXiv:2609.00742v1 Announce Type: new Abstract: As AI video generators achieve cinematic realism, reliable detection becomes essential for safeguarding digital trust. We identify cross-scale coupling mismatch as a new fo…

arXiv (cs)1h ago
Dastawez Jahan-Numa

The Price of Remembering: A Calibrated Energy Law for Computation

arXiv:2609.00744v2 Announce Type: new Abstract: Where does a computer's energy go? Mostly into keeping, not into computing. A bit held in fast storage draws power for every second it stays there, and it costs energy agai…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Feed-Forward Multi-view Multi-person Reconstruction with Contrastive Human-Aware 3D Representation

arXiv:2609.00745v1 Announce Type: new Abstract: Multi-view human reconstruction has been extensively studied under simplified settings, yet robust and efficient multi-person reconstruction in unconstrained environments r…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Text Capability Loss in Vision-Language Adaptation: An Attention-Sink Diagnosis

arXiv:2609.00746v1 Announce Type: new Abstract: Fine-tuning a pretrained LLM into a vision-language model (VLM) can erode the backbone's text capability, with the damage concentrated on tasks that require following exact…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Can Large Language Models Forecast What Researchers Study Next?

arXiv:2609.00747v1 Announce Type: new Abstract: Large language models increasingly generate research ideas, yet judging their novelty or feasibility at generation time does not establish whether they anticipate subsequen…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Measuring Optimal Transport in Transformer Depth

arXiv:2609.00748v1 Announce Type: new Abstract: A transformer carries each token's state from layer to layer, and the whole vocabulary carried together forms a cloud that moves with depth. We ask whether a trained networ…

arXiv (cs)1h ago
Dastawez Jahan-Numa

ContextPipe: Database-Inspired Context Assembly for Long-Horizon Agents

arXiv:2609.00749v1 Announce Type: new Abstract: Long-horizon large language model (LLM) agents require context assembly: the runtime must decide what to include in each prompt, in what order, and when to compact history …

arXiv (cs)1h ago
Dastawez Jahan-Numa

One Print, Many Moves: Monolithic Origami-inspired Folding Actuator for Composable Soft Multi-DoF Systems

arXiv:2609.00751v1 Announce Type: new Abstract: Conventional soft robot actuators excel in compliance, but their uncontrolled deformations compromise accuracy and hinder scaling to multi-degree-of-freedom (DoF) systems. …

arXiv (cs)1h ago
Dastawez Jahan-Numa

How Do Language Models Choose Between Context and Memory?

arXiv:2609.00753v1 Announce Type: new Abstract: When contextual information conflicts with the knowledge stored in model parameters, activation directions can be used to decode and steer which source the model follows. H…

arXiv (cs)1h ago
Dastawez Jahan-Numa

S^3martCirc: Self-supervised Smart Circuit Discovery

arXiv:2609.00755v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks, from text summarization to question answering. Despite these capabilities, their…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Joint Training Is Not Enough: Conditioned Cross-Granularity Training for Multimodal Document Understanding

arXiv:2609.00756v1 Announce Type: new Abstract: The Mutual Reinforcement Effect (MRE) asks whether a fine, span-level and a coarse, document-level task help each other when one model handles both. We test it in multimoda…

arXiv (cs)1h ago
Dastawez Jahan-Numa

Compile, Don't Memorize: A Context Compilation Architecture (CCA) for In-Context Learning

arXiv:2609.00759v1 Announce Type: new Abstract: Large language models (LLMs) increasingly handle in-context learning (ICL) tasks where a long, novel context defines the rules, knowledge, and output schema for a series of…

arXiv (cs)1h ago
Dastawez Jahan-Numa

A Unified Mechanistic Analysis of Knowledge- and Safety-Based Refusals

arXiv:2609.00760v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly trained to decline queries that fall outside their knowledge (knowledge-based refusal, KR) or violate safety policies (safety-…

arXiv (cs)1h ago
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