Tootfinder

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[3/4]:
- Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency
Chenlong Wang, Yuanning Feng, Dongping Chen, Zhaoyang Chu, Ranjay Krishna, Tianyi Zhou

In-Context Learning for Gradient-Free Receiver Adaptation: Principles, Applications, and Theory
Matteo Zecchin, Tomer Raviv, Dileep Kalathil, Krishna Narayanan, Nir Shlezinger, Osvaldo Simeone
https://arxiv.org/abs/2506.15176

In-Context Learning for Gradient-Free Receiver Adaptation: Principles, Applications, and Theory
In recent years, deep learning has facilitated the creation of wireless receivers capable of functioning effectively in conditions that challenge traditional model-based designs. Leveraging programmable hardware architectures, deep learning-based receivers offer the potential to dynamically adapt to varying channel environments. However, current adaptation strategies, including joint training, hypernetwork-based methods, and meta-learning, either demonstrate limited flexibility or necessitate e…

Physics constrained learning of stochastic characteristics
Pardha Sai Krishna Ala, Ameya Salvi, Venkat Krovi, Matthias Schmid
https://arxiv.org/abs/2507.12661

Physics constrained learning of stochastic characteristics
Accurate state estimation requires careful consideration of uncertainty surrounding the process and measurement models; these characteristics are usually not well-known and need an experienced designer to select the covariance matrices. An error in the selection of covariance matrices could impact the accuracy of the estimation algorithm and may sometimes cause the filter to diverge. Identifying noise characteristics has long been a challenging problem due to uncertainty surrounding noise sourc…

Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation
Carolina Higuera, Akash Sharma, Taosha Fan, Chaithanya Krishna Bodduluri, Byron Boots, Michael Kaess, Mike Lambeta, Tingfan Wu, Zixi Liu, Francois Robert Hogan, Mustafa Mukadam
https://arxiv.org/abs/2506.14754…

Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation
We present Sparsh-X, the first multisensory touch representations across four tactile modalities: image, audio, motion, and pressure. Trained on ~1M contact-rich interactions collected with the Digit 360 sensor, Sparsh-X captures complementary touch signals at diverse temporal and spatial scales. By leveraging self-supervised learning, Sparsh-X fuses these modalities into a unified representation that captures physical properties useful for robot manipulation tasks. We study how to effectively …

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Jody Stecher and Krishna Bhatt:
🎵 The Bramble an the Rose
#JodyStecherandKrishnaBhatt
https://open.spotify.com/track/3fCETTD0PKGIOFUzQxw7UJ

Polycyclic Aromatic Hydrocarbons in the circumstellar medium of Herbig Ae/Be stars
R. Arun, Blesson Mathew, B. Shridharan, K. Ujjwal, Akhil Krishna R, G. Maheswar, Sreeja S. Kartha
https://arxiv.org/abs/2506.14218

Polycyclic Aromatic Hydrocarbons in the circumstellar medium of Herbig Ae/Be stars
We present a comprehensive mid-infrared spectroscopic survey of 124 Herbig Ae/Be stars using newly processed Spitzer/IRS spectra from the newly released CASSISjuice database. Based on prominent dust and molecular signatures (polycyclic aromatic hydrocarbons, silicates, and hydrogenated amorphous carbons), we classify the stars into five groups. Our analysis reveals that 64% of the spectra show PAH emission, with detections peaking in the stellar effective temperature range 7000-11000 K (B9-A5).…

Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering
Muhammad Fadhil Ginting, Dong-Ki Kim, Xiangyun Meng, Andrzej Reinke, Bandi Jai Krishna, Navid Kayhani, Oriana Peltzer, David D. Fan, Amirreza Shaban, Sung-Kyun Kim, Mykel J. Kochenderfer, Ali-akbar Agha-mohammadi, Shayegan Omidshafiei
https://

Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering
As robots become increasingly capable of operating over extended periods -- spanning days, weeks, and even months -- they are expected to accumulate knowledge of their environments and leverage this experience to assist humans more effectively. This paper studies the problem of Long-term Active Embodied Question Answering (LA-EQA), a new task in which a robot must both recall past experiences and actively explore its environment to answer complex, temporally-grounded questions. Unlike tradition…

Reversible Pebble Transducers
Luc Dartois, Paul Gastin, L. Germerie Guizouarn, Shankaranarayanan Krishna
https://arxiv.org/abs/2506.11334 https://

Reversible Pebble Transducers
Deterministic two-way transducers with pebbles (aka pebble transducers) capture the class of polyregular functions, which extend the string-to-string regular functions allowing polynomial growth instead of linear growth. One of the most fundamental operations on functions is composition, and (poly)regular functions can be realized as a composition of several simpler functions. In general, composition of deterministic two-way transducers incur a doubly exponential blow-up in the size of the inpu…

Machine Intelligence on Wireless Edge Networks
Sri Krishna Vadlamani, Kfir Sulimany, Zhihui Gao, Tingjun Chen, Dirk Englund
https://arxiv.org/abs/2506.12210

Machine Intelligence on Wireless Edge Networks
Deep neural network (DNN) inference on power-constrained edge devices is bottlenecked by costly weight storage and data movement. We introduce MIWEN, a radio-frequency (RF) analog architecture that ``disaggregates'' memory by streaming weights wirelessly and performing classification in the analog front end of standard transceivers. By encoding weights and activations onto RF carriers and using native mixers as computation units, MIWEN eliminates local weight memory and the overhead of analog-t…

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models
Arjun R. Akula, Kazuma Hashimoto, Krishna Srinivasan, Aditi Chaudhary, Karthik Raman, Michael Bendersky
https://arxiv.org/abs/2506.12346

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models
The emergence of long-context large language models (LLMs) has enabled the use of hundreds, or even thousands, of demonstrations for in-context learning (ICL) - a previously impractical regime. This paper investigates whether traditional ICL selection strategies, which balance the similarity of ICL examples to the test input (using a text retriever) with diversity within the ICL set, remain effective when utilizing a large number of demonstrations. Our experiments demonstrate that, while longer…

A Topic Modeling Analysis of Stigma Dimensions, Social, and Related Behavioral Circumstances in Clinical Notes Among Patients with HIV
Ziyi Chen, Yiyang Liu, Mattia Prosperi, Krishna Vaddiparti, Robert L Cook, Jiang Bian, Yi Guo, Yonghui Wu
https://arxiv.org/abs/2506.09279

A Topic Modeling Analysis of Stigma Dimensions, Social, and Related Behavioral Circumstances in Clinical Notes Among Patients with HIV
Objective: To characterize stigma dimensions, social, and related behavioral circumstances in people living with HIV (PLWHs) seeking care, using natural language processing methods applied to a large collection of electronic health record (EHR) clinical notes from a large integrated health system in the southeast United States. Methods: We identified 9,140 cohort of PLWHs from the UF Health IDR and performed topic modeling analysis using Latent Dirichlet Allocation (LDA) to uncover stigma dimen…

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Vinaik Chhetri, Krishna Upadhyay, A. B. Siddique, Umar Farooq
https://arxiv.org/abs/2506.10785

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Artificial Intelligence (AI)-powered features have rapidly proliferated across mobile apps in various domains, including productivity, education, entertainment, and creativity. However, how users perceive, evaluate, and critique these AI features remains largely unexplored, primarily due to the overwhelming volume of user feedback. In this work, we present the first comprehensive, large-scale study of user feedback on AI-powered mobile apps, leveraging a curated dataset of 292 AI-driven apps ac…

Upper bounds for Erd\'{e}lyi's multivariate Laguerre polynomials
Min-Jie Luo, Ravinder Krishna Raina
https://arxiv.org/abs/2507.11024 https://

Upper bounds for Erdélyi's multivariate Laguerre polynomials
We establish in this paper two inequalities for the multivariate Laguerre polynomials introduced and studied by Arthur Erdélyi [Sitzungsber. Akad. Wiss. Wien, Math.-Naturw. Kl., Abt. IIa 146 (1937), 431--467]. These inequalities generalize the well-known Szegö's inequality for the Laguerre polynomials $L_n^{(α)}(x)$. We also mention briefly few insightful remarks giving a comparative analysis concerning the upper bounds of the derived inequalities in the concluding section.

Band Meandering due to Charged Impurity Effects and Carrier Transport in Ternary Topological Insulators
Kanav Sharma, Niranjay K R, Radha Krishna Gopal, Chiranjib Mitra
https://arxiv.org/abs/2507.08579

Band Meandering due to Charged Impurity Effects and Carrier Transport in Ternary Topological Insulators
In this study, we investigated the impact of charged impurities on the electrical properties of the topological insulator $\left(\mathrm{Bi}_{0.3} \mathrm{Sb}_{0.7}\right)_2 \mathrm{Te}_3$ (BST) and its indium-doped counterpart, $\mathrm{In}_{0.14}\left(\mathrm{Bi}_{0.3} \mathrm{Sb}_{0.7}\right)_{1.86} \mathrm{Te}_3$ (IBST), using field-effect gating. For thin BST (30 nm), charged impurities, potentially from silicon dioxide substrate traps, contribute to band tail-type localization, with the i…

Fortunate to see up close this "alankaara" in person yesterday (Thursday).
#Udupi #Krishna #India

Efficient Task Graph Scheduling for Parallel QR Factorization in SLSQP
Soumyajit Chatterjee, Rahul Utkoor, Uppu Eshwar, Sathya Peri, V. Krishna Nandivada
https://arxiv.org/abs/2506.09463

Efficient Task Graph Scheduling for Parallel QR Factorization in SLSQP
Efficient task scheduling is paramount in parallel programming on multi-core architectures, where tasks are fundamental computational units. QR factorization is a critical sub-routine in Sequential Least Squares Quadratic Programming (SLSQP) for solving non-linear programming (NLP) problems. QR factorization decomposes a matrix into an orthogonal matrix Q and an upper triangular matrix R, which are essential for solving systems of linear equations arising from optimization problems. SLSQP uses …

Fine-Grained control over Music Generation with Activation Steering
Dipanshu Panda, Jayden Koshy Joe, Harshith M R, Swathi Narashiman, Pranay Mathur, Anish Veerakumar, Aniruddh Krishna, Keerthiharan A
https://arxiv.org/abs/2506.10225

Fine-Grained control over Music Generation with Activation Steering
We present a method for fine-grained control over music generation through inference-time interventions on an autoregressive generative music transformer called MusicGen. Our approach enables timbre transfer, style transfer, and genre fusion by steering the residual stream using weights of linear probes trained on it, or by steering the attention layer activations in a similar manner. We observe that modelling this as a regression task provides improved performance, hypothesizing that the mean-…

Fuzzy Lattice-based Description Logic
Yiwen Ding, Krishna Manoorkar
https://arxiv.org/abs/2506.05833 https://arxiv.org/pdf/2506.05833…

Fuzzy Lattice-based Description Logic
Recently, description logic LE-ALC was introduced for reasoning in the semantic environment of enriched formal contexts, and a polynomial-time tableaux algorithm was developed to check the consistency of knowledge bases with acyclic TBoxes. In this work, we introduce a fuzzy generalization of LE-ALC called LE-FALC which provides a description logic counterpart of many-valued normal non-distributive logic a.k.a. many-valued LE-logic. This description logic can be used to represent and reason a…

PotentRegion4MalDetect: Advanced Features from Potential Malicious Regions for Malware Detection
Rama Krishna Koppanati, Monika Santra, Sateesh Kumar Peddoju
https://arxiv.org/abs/2507.06723

PotentRegion4MalDetect: Advanced Features from Potential Malicious Regions for Malware Detection
Malware developers exploit the fact that most detection models focus on the entire binary to extract the feature rather than on the regions of potential maliciousness. Therefore, they reverse engineer a benign binary and inject malicious code into it. This obfuscation technique circumvents the malware detection models and deceives the ML classifiers due to the prevalence of benign features compared to malicious features. However, extracting the features from the potential malicious regions enha…

Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Chun-Hsiao Yeh, Yilin Wang, Nanxuan Zhao, Richard Zhang, Yuheng Li, Yi Ma, Krishna Kumar Singh
https://arxiv.org/abs/2507.05259

Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Recent diffusion-based image editing methods have significantly advanced text-guided tasks but often struggle to interpret complex, indirect instructions. Moreover, current models frequently suffer from poor identity preservation, unintended edits, or rely heavily on manual masks. To address these challenges, we introduce X-Planner, a Multimodal Large Language Model (MLLM)-based planning system that effectively bridges user intent with editing model capabilities. X-Planner employs chain-of-thou…

The Roasting Marshmallows Program with IGRINS on Gemini South III: Seeing deeper into the metal depleted atmosphere of a gas-giant on the cusp of the hot to ultra-hot Jupiter transition
Vatsal Panwar, Matteo Brogi, Krishna Kanumalla, Michael R. Line, Siddharth Gandhi, Peter C. B. Smith, Jacob L. Bean, Lorenzo Pino, Arjun B. Savel, Joost P. Wardenier, Heather Cegla, Hayley Beltz, Megan Weiner Mansfield, Jorge A. Sanchez, Jean-Michel D\'esert, Luis Welbanks, Viven Parmentier, Changwo…

The Roasting Marshmallows Program with IGRINS on Gemini South III: Seeing deeper into the metal depleted atmosphere of a gas-giant on the cusp of the hot to ultra-hot Jupiter transition
Ultra-hot Jupiters are a class of gas-giant exoplanets that show a peculiar combination of thermochemical properties in the form of molecular dissociation, atomic ionization, and inverted thermal structures. Atmospheric characterization of gas giants lying in the transitional regime between hot and ultra-hot Jupiters can help in understanding the physical mechanisms that cause the fundamental transition in atmospheres between the two classes of hot gas giants. Using Doppler spectroscopy with IG…

Learning to Transmit Over Unknown Erasure Channels with Empirical Erasure Rate Feedback
Haricharan Balasundaram, Krishna Jagannathan
https://arxiv.org/abs/2507.08599

Learning to Transmit Over Unknown Erasure Channels with Empirical Erasure Rate Feedback
We address the problem of reliable data transmission within a finite time horizon $T$ over a binary erasure channel with unknown erasure probability. We consider a feedback model wherein the transmitter can query the receiver infrequently and obtain the empirical erasure rate experienced by the latter. We aim to minimize a regret quantity, i.e. how much worse a strategy performs compared to an oracle who knows the probability of erasure, while operating at the same block error rate. A learning …

Correlative angstrom-scale microscopy and spectroscopy of graphite-water interfaces
Lalith Krishna Samanth Bonagiri, Diana M. Arvelo, Fujia Zhao, Jaehyeon Kim, Qian Ai, Shan Zhou, Kaustubh S. Panse, Ricardo Garcia, Yingjie Zhang
https://arxiv.org/abs/2506.09908

Correlative angstrom-scale microscopy and spectroscopy of graphite-water interfaces
Water at solid surfaces is key for many processes ranging from biological signal transduction to membrane separation and renewable energy conversion. However, under realistic conditions, which often include environmental and surface charge variations, the interfacial water structure remains elusive. Here we overcome this limit by combining three-dimensional atomic force microscopy and interface-sensitive Raman spectroscopy to characterize the graphite-water interfacial structure in situ. Throug…

OLAF: Programmable Data Plane Acceleration for Asynchronous Distributed Reinforcement Learning
Nehal Baganal Krishna, Anam Tahir, Firas Khamis, Mina Tahmasbi Arashloo, Michael Zink, Amr Rizk
https://arxiv.org/abs/2507.05876

OLAF: Programmable Data Plane Acceleration for Asynchronous Distributed Reinforcement Learning
Asynchronous Distributed Reinforcement Learning (DRL) can suffer from degraded convergence when model updates become stale, often the result of network congestion and packet loss during large-scale training. This work introduces a network data-plane acceleration architecture that mitigates such staleness by enabling inline processing of DRL model updates as they traverse the accelerator engine. To this end, we design and prototype a novel queueing mechanism that opportunistically combines compa…

Modeling the Multiwavelength Emission of 3C 279 during the 14 years of Fermi-LAT Era
Krishna Mohana A, Alok C. Gupta, Junhui Fan, Narek Sahakyan, Claudia M. Raiteri, Lang Cui, Anne Lahteenmaki, Mark Gurwell, Merja Tornikoski, Massimo Villata
https://arxiv.org/abs/2507.03913

Modeling the Multiwavelength Emission of 3C 279 during the 14 years of Fermi-LAT Era
We report the results of our long-term multiwavelength spectral energy distribution (SED) study on the flat spectrum radio quasar 3C 279 during the $\sim14$ years (2008--2022) of {\sl Fermi}-LAT (Large Area Telescope) observing period. The {\sl Fermi}-LAT data were complemented with data in other wavebands obtained from {\sl Swift}-XRT/UVOT, Whole Earth Blazar Telescope (WEBT), along with other optical and radio data from several observatories. Different activity states were identified from the…

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory
Zheng, Zhang, Salehi, Gao, Iyengar, Kobori, Kong, Krishna

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents
Sanjay Krishna Anbalagan, Xinrui Nie, Umesh Mohan, Vijay Kumar Kanamarlapudi, Anughna Kommalapati, Xiaodan Zhao
https://arxiv.org/abs/2507.01862

Bridging UI Design and chatbot Interactions: Applying Form-Based Principles to Conversational Agents
Domain specific chatbot applications often involve multi step interactions, such as refining search filters, selecting multiple items, or performing comparisons. Traditional graphical user interfaces (GUIs) handle these workflows by providing explicit "Submit" (commit data) and "Reset" (discard data) actions, allowing back-end systems to track user intent unambiguously. In contrast, conversational agents rely on subtle language cues, which can lead to confusion and incomplete context management…

Is there a Larks Tongues in Aspic Day?
If there were then it should probably be 23rd of March but if there isn't it's today, May 27th.
Not because of the 27 Club
Not because of the Martin 27 Guitar
Nor that 27 is a perfect cube
Or that 27ish C is a comfortable degree of heat
Neither is it that 27 in the Correspondences of Liber 777 is Red, Horus, Krishna, Mars, Ruby or Mouth, etc
It's just because I thought it today.

On the Conjecture of the Representation Number of Bipartite Graphs
Khyodeno Mozhui, K. V. Krishna
https://arxiv.org/abs/2506.01057 https://

On the Conjecture of the Representation Number of Bipartite Graphs
While the problem of determining the representation number of an arbitrary word-representable graph is NP-hard, this problem is open even for bipartite graphs. The representation numbers are known for certain bipartite graphs including all the graphs with at most nine vertices. For bipartite graphs with partite sets of sizes $m$ and $n$, Glen et al. conjectured that the representation number is at most $\lceil \frac{m+n}{4}\rceil$, where $m+n \ge 9$. In this paper, we show that every bipartit…

Evaluating the Critical Risks of Amazon's Nova Premier under the Frontier Model Safety Framework
Satyapriya Krishna, Ninareh Mehrabi, Abhinav Mohanty, Matteo Memelli, Vincent Ponzo, Payal Motwani, Rahul Gupta
https://arxiv.org/abs/2507.06260

Evaluating the Critical Risks of Amazon's Nova Premier under the Frontier Model Safety Framework
Nova Premier is Amazon's most capable multimodal foundation model and teacher for model distillation. It processes text, images, and video with a one-million-token context window, enabling analysis of large codebases, 400-page documents, and 90-minute videos in a single prompt. We present the first comprehensive evaluation of Nova Premier's critical risk profile under the Frontier Model Safety Framework. Evaluations target three high-risk domains -- Chemical, Biological, Radiological & Nuclear …

GLoSS: Generative Language Models with Semantic Search for Sequential Recommendation
Krishna Acharya, Aleksandr V. Petrov, Juba Ziani
https://arxiv.org/abs/2506.01910

GLoSS: Generative Language Models with Semantic Search for Sequential Recommendation
We propose Generative Low-rank language model with Semantic Search (GLoSS), a generative recommendation framework that combines large language models with dense retrieval for sequential recommendation. Unlike prior methods such as GPT4Rec, which rely on lexical matching via BM25, GLoSS uses semantic search to retrieve relevant items beyond lexical matching. For query generation, we employ 4-bit quantized LlaMA-3 models fine-tuned with low-rank adaptation (LoRA), enabling efficient training and …

Generalizable, real-time neural decoding with hybrid state-space models
Avery Hee-Woon Ryoo, Nanda H. Krishna, Ximeng Mao, Mehdi Azabou, Eva L. Dyer, Matthew G. Perich, Guillaume Lajoie
https://arxiv.org/abs/2506.05320

Generalizable, real-time neural decoding with hybrid state-space models
Real-time decoding of neural activity is central to neuroscience and neurotechnology applications, from closed-loop experiments to brain-computer interfaces, where models are subject to strict latency constraints. Traditional methods, including simple recurrent neural networks, are fast and lightweight but often struggle to generalize to unseen data. In contrast, recent Transformer-based approaches leverage large-scale pretraining for strong generalization performance, but typically have much l…

Revealing a transitional epoch of large-scale cosmic anisotropy in the quasar distribution
Amit Mondal, Biswajit Pandey, Krishna Ghosh
https://arxiv.org/abs/2507.02835

Revealing a transitional epoch of large-scale cosmic anisotropy in the quasar distribution
The Cosmological Principle posits that the Universe is isotropic on the largest scales. While widely supported, this foundational assumption remains testable. We analyse the angular distribution of over one million quasars from the Gaia-unWISE catalogue using Renyi entropy, a multiscale statistical measure sensitive to higher-order clustering. Dividing the sample into three redshift bins, we find that both the low- and high-redshift distributions are statistically consistent with isotropy. Howe…

pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization
Mrinmay Sen, Chalavadi Krishna Mohan
https://arxiv.org/abs/2506.07159

pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization
Personalized Federated Learning (PFL) enables clients to collaboratively train personalized models tailored to their individual objectives, addressing the challenge of model generalization in traditional Federated Learning (FL) due to high data heterogeneity. However, existing PFL methods often require increased communication rounds to achieve the desired performance, primarily due to slow training caused by the use of first-order optimization, which has linear convergence. Additionally, many o…

📚 Wie gelingt verständliche Kommunikation in Bibliotheken?
Am 7. Mai (9:30–13 Uhr) zeigt Krishna-Sara Helmle im Online-Seminar, wie Einfache Sprache funktioniert – praxisnah, inkl. KI-Tipps und Arbeit mit eigenen Texten.
Anmelden: https://dgi-info.de/event/einfache…

3HDM at the ILC
Baradhwaj Coleppa, Akshat Khanna, Gokul B. Krishna
https://arxiv.org/abs/2506.24094 https://arxiv.org/pdf/2506.24094

3HDM at the ILC
The Three-Higgs-Doublet Model (3HDM) extends the Standard Model by introducing two additional scalar doublets, leading to a rich spectrum of new particles: three neutral CP-even Higgs bosons ($h_1$, $H_2$, $H_3$), two neutral CP-odd Higgs bosons ($A_2$, $A_3$), and two charged Higgs bosons ($H_2^+$, $H_3^+$). In this work, we present a phenomenological study of the 3HDM at the future International Linear Collider (ILC) with a center-of-mass energy of $\sqrt{s} = 1000\,\text{GeV}$. Applying a co…

Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering
Krishna Ronanki, Simon Arvidsson, Johan Axell
https://arxiv.org/abs/2507.03405

Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering
The rapid emergence of generative AI models like Large Language Models (LLMs) has demonstrated its utility across various activities, including within Requirements Engineering (RE). Ensuring the quality and accuracy of LLM-generated output is critical, with prompt engineering serving as a key technique to guide model responses. However, existing literature provides limited guidance on how prompt engineering can be leveraged, specifically for RE activities. The objective of this study is to expl…

Replaced article(s) found for eess.AS. https://arxiv.org/list/eess.AS/new
[1/1]:
- Rethinking Non-Negative Matrix Factorization with Implicit Neural Representations
Krishna Subramani, Paris Smaragdis, Takuya Higuchi, Mehrez Souden

What you do with this information is up to you, but whatever you do, I assume you do responsibly. 😆
BTW Krishna Navami is the 9th day of the waning moon phase. The next one is on this 19th (and every 28-30 days thereafter).
Excerpt from: #trivia #cheeky #calendar

Fluid Democracy in Federated Data Aggregation
Aditya Vema Reddy Kesari, Krishna Reddy Kesari
https://arxiv.org/abs/2507.02710 https://

Fluid Democracy in Federated Data Aggregation
Federated learning (FL) mechanisms typically require each client to transfer their weights to a central server, irrespective of how useful they are. In order to avoid wasteful data transfer costs from clients to the central server, we propose the use of consensus based protocols to identify a subset of clients with most useful model weights at each data transfer step. First, we explore the application of existing fluid democracy protocols to FL from a performance standpoint, comparing them with…

A network-theoretic approach for characterizing Mack-mode instability in high-speed boundary layers
Sai Prasad Mohanty, Nikhil Khobragade, Gaurav Chopra, Aswathi Krishna, R. I. Sujith, Subrahmanyam Duvvuri
https://arxiv.org/abs/2507.00370

A network-theoretic approach for characterizing Mack-mode instability in high-speed boundary layers
Here we present a network theory-based approach to investigate the Mack-mode instability signature found in high-speed schlieren data from a Mach 6 laminar boundary layer flow over a $7^\circ$ cone. The data contain instability wave packets in the form of coherent rope-like structures which exhibit intermittency. The intermittency implies that conventional Fourier techniques are not particularly well suited for analysis. Network analysis, which is well known for handling episodic spatio-tempora…

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/1]:
- Adaptive Modified RISE Control for Quadrotors: Enhancing Trajectory Tracking Through Uncertainty ...
Kevin Johnston, Musabbir Ahmed Arrafi, Krishna B Kidambi, Madhur Tiwari

Properties of slow magneto-acoustic waves observed simultaneously using Hi-C 2.1 and AIA
Suraj K. Tripathy, S. Krishna Prasad, D. Banerjee
https://arxiv.org/abs/2506.06126

Properties of slow magneto-acoustic waves observed simultaneously using Hi-C 2.1 and AIA
Propagating slow magneto-acoustic waves are commonly observed in different coronal structures but are most prominent in active region fan loops. Their rapid damping with damping lengths of the order of a wavelength has been investigated in the past by several authors. Although different physical mechanisms have been proposed, significant discrepancies between the theory and observations remain. Recent high-resolution observations captured simultaneously by two different instruments reveal disti…

RefTok: Reference-Based Tokenization for Video Generation
Xiang Fan, Xiaohang Sun, Kushan Thakkar, Zhu Liu, Vimal Bhat, Ranjay Krishna, Xiang Hao
https://arxiv.org/abs/2507.02862 …

RefTok: Reference-Based Tokenization for Video Generation
Effectively handling temporal redundancy remains a key challenge in learning video models. Prevailing approaches often treat each set of frames independently, failing to effectively capture the temporal dependencies and redundancies inherent in videos. To address this limitation, we introduce RefTok, a novel reference-based tokenization method capable of capturing complex temporal dynamics and contextual information. Our method encodes and decodes sets of frames conditioned on an unquantized re…

Cool Gas in the Circumgalactic Medium of Massive Post Starburst Galaxies
Zoe Harvey, Sahyadri Krishna, Vivienne Wild, Rita Tojeiro, Paul Hewett
https://arxiv.org/abs/2506.22287

Cool Gas in the Circumgalactic Medium of Massive Post Starburst Galaxies
Observing the interplay between galaxies and their gaseous surroundings is crucial for understanding how galaxies form and evolve, including the roles of long-lived cool gas reservoirs, starburst and AGN driven outflows. We use stacked Mg II absorption lines in the spectra of background quasars to study the cool gas out to 9Mpc from massive quiescent, star-forming and post-starburst galaxies with stellar masses $\log_{10}(M_{\mathrm{gal}}/M_\odot) \gtrsim 11.4$ and $0.4 \lesssim z \lesssim 0.8$…

Questions as cognitive filters
Willem Conradie, Krishna Manoorkar, Alessandra Palmigiano, Apostolos Tzimoulis, Nachoem Wijnberg
https://arxiv.org/abs/2506.22735

Questions as cognitive filters
In this paper, we develop a logico-algebraic framework for modeling decision-making through deliberation in multi-agent settings. The central concept in this framework is that of interrogative agendas, which represent the cognitive stances of agents regarding which features should be considered relevant in the final decision. We formalize an agent's interrogative agenda as an equivalence relation that identifies outcomes differing only in aspects the agent deems irrelevant. Moreover, we charact…

A composite of the effects of major sudden stratospheric warming events on carbon dioxide radiative cooling in the mesosphere-lower-thermosphere
Akash Kumar, MV Sunil Krishna, Alok K Ranjan
https://arxiv.org/abs/2506.23764

A composite of the effects of major sudden stratospheric warming events on carbon dioxide radiative cooling in the mesosphere-lower-thermosphere
The major sudden stratospheric warming (SSW) events strongly influence the mean structure of the entire atmosphere, from the troposphere to the thermosphere. These events disrupt the compositional and thermal structure of the mesosphere and lower thermosphere (MLT), causing spatiotemporal variations in the concentration of trace species of this region. Currently, the role of dynamical changes during SSW events on radiative cooling in the MLT region is not well understood. An investigation of th…

Fairness Dynamics During Training
Krishna Patel, Nivedha Sivakumar, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
https://arxiv.org/abs/2506.01709

Fairness Dynamics During Training
We investigate fairness dynamics during Large Language Model (LLM) training to enable the diagnoses of biases and mitigations through training interventions like early stopping; we find that biases can emerge suddenly and do not always follow common performance metrics. We introduce two new metrics to evaluate fairness dynamics holistically during model pre-training: Average Rank and Jensen-Shannon Divergence by Parts. These metrics provide insights into the Pythia models' progression of biases…

p-adic Ghobber-Jaming Uncertainty Principle
K. Mahesh Krishna
https://arxiv.org/abs/2506.18913 https://arxiv.org/pdf/2506.18913

p-adic Ghobber-Jaming Uncertainty Principle
Let $\{τ_j\}_{j=1}^n$ and $\{ω_k\}_{k=1}^n$ be two orthonormal bases for a finite dimensional p-adic Hilbert space $\mathcal{X}$. Let $M,N\subseteq \{1, \dots, n\}$ be such that \begin{align*} \displaystyle \max_{j \in M, k \in N}|\langle τ_j, ω_k \rangle|<1, \end{align*} where $o(M)$ is the cardinality of $M$. Then for all $x \in \mathcal{X}$, we show that \begin{align} (1) \quad \quad \quad \quad \|x\|\leq \left(\frac{1}{1-\displaystyle \max_{j \in M, k \in N}|\la…

PII Jailbreaking in LLMs via Activation Steering Reveals Personal Information Leakage
Krishna Kanth Nakka, Xue Jiang, Xuebing Zhou
https://arxiv.org/abs/2507.02332

PII Jailbreaking in LLMs via Activation Steering Reveals Personal Information Leakage
This paper investigates privacy jailbreaking in LLMs via steering, focusing on whether manipulating activations can bypass LLM alignment and alter response behaviors to privacy related queries (e.g., a certain public figure's sexual orientation). We begin by identifying attention heads predictive of refusal behavior for private attributes (e.g., sexual orientation) using lightweight linear probes trained with privacy evaluator labels. Next, we steer the activations of a small subset of these at…

Unlocking the hybrid piezo and pyroelectric nanogenerators performance by SiO2 nanowires confinement in poly(vinylidene fluoride)
Juan Delgado-Alvarez, Hari Krishna Mishra, Francisco J. Aparicio, Xabier Garcia-Casas, Angel Barranco, Juan R. Sanchez-Valencia, Victor Lopez-Flores, Ana Borras
https://arxiv.org/abs/2506.01580…

Unlocking the hybrid piezo and pyroelectric nanogenerators performance by SiO2 nanowires confinement in poly(vinylidene fluoride)
We report on the development of a novel flexible piezo/pyro-electric nanogenerator (PPNG) that combines a uniform film of poly(vinylidene fluoride) (PVDF) infiltrated over vertically supported SiO2 nanowires (NWs) to enhance both piezoelectric and pyroelectric energy harvesting capabilities. The synthetic procedure involves a low-temperature multi-step approach, including the soft-template formation of SiO2 NWs on a flexible substrate, followed by the infiltration of a PVDF thin film (TF). The …

Structural Code Search using Natural Language Queries
Ben Limpanukorn, Yanjun Wang, Zach Patterson, Pranav Garg, Murali Krishna Ramanathan, Xiaofei Ma, Anoop Deoras, Miryung Kim
https://arxiv.org/abs/2507.02107

Structural Code Search using Natural Language Queries
Searching code is a common task that developers perform to understand APIs, learn common code patterns, and navigate code. Currently, developers most commonly search using keywords and regular expressions that are easy to use and widely available. Beyond keywords and regular expressions, structural code search tools allow developers to search for code based on its syntactic structure. This has numerous applications ranging from bug finding to systematically refactoring code. However, these stru…

RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation
Yi Ru Wang, Carter Ung, Grant Tannert, Jiafei Duan, Josephine Li, Amy Le, Rishabh Oswal, Markus Grotz, Wilbert Pumacay, Yuquan Deng, Ranjay Krishna, Dieter Fox, Siddhartha Srinivasa
https://arxiv.org/abs/2507.00435…

RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation
We present RoboEval, a simulation benchmark and structured evaluation framework designed to reveal the limitations of current bimanual manipulation policies. While prior benchmarks report only binary task success, we show that such metrics often conceal critical weaknesses in policy behavior -- such as poor coordination, slipping during grasping, or asymmetric arm usage. RoboEval introduces a suite of tiered, semantically grounded tasks decomposed into skill-specific stages, with variations tha…

BACTA-GPT: An AI-Based Bayesian Adaptive Clinical Trial Architect
Krishna Padmanabhan, Danny Baker
https://arxiv.org/abs/2507.02130 https://

BACTA-GPT: An AI-Based Bayesian Adaptive Clinical Trial Architect
Bayesian adaptive clinical trials offer a flexible and efficient alternative to traditional fixed-design trials, but their implementation is often hindered by the complexity of Bayesian computations and the need for advanced statistical programming expertise. The authors introduce a custom fine-tuned LLM designed to assist with this and lower barriers to adoption of Bayesian methods for adaptive clinical trials. This paper describes the development and fine-tuning of BACTA-GPT, a Large Language…

ISI-Aware Code Design: A Linear Approach Towards Reliable Molecular Communication
Tamoghno Nath, Krishna Gopal Benerjee, Adrish Banerjee
https://arxiv.org/abs/2506.23787

ISI-Aware Code Design: A Linear Approach Towards Reliable Molecular Communication
Intersymbol Interference (ISI) is a major bottleneck in Molecular Communication via Diffusion (MCvD), degrading system performance. This paper introduces two families of linear channel codes to mitigate ISI: Zero Pad Zero Start (ZPZS) and Zero Pad (ZP) codes, ensuring that each codeword avoids consecutive bit-1s. The ZPZS and ZP codes are then combined to form a binary ZP code, offering a higher code rate than linear ZP codes and allowing simple decoding via the Majority Location Rule (MLR). Ad…

Discrete-Time Linear Dynamical System Control Using Sparse Inputs With Time-Varying Support
Krishna Praveen V. S. Kondapi, Chandrasekhar Sriram, Geethu Joseph, Chandra R. Murthy
https://arxiv.org/abs/2506.18514

Discrete-Time Linear Dynamical System Control Using Sparse Inputs With Time-Varying Support
In networked control systems, communication resource constraints often necessitate the use of \emph{sparse} control input vectors. A prototypical problem is how to ensure controllability of a linear dynamical system when only a limited number of actuators (inputs) can be active at each time step. In this work, we first present an algorithm for determining the \emph{sparse actuator schedule}, i.e., the sequence of supports of the input vectors that ensures controllability. Next, we extend the al…

Thermal transport characteristics of impinging ferrofluid droplets in the presence of a magnetic field
Ram Krishna Shah
https://arxiv.org/abs/2506.20284 ht…

Thermal transport characteristics of impinging ferrofluid droplets in the presence of a magnetic field
Droplet interactions with solid surfaces are fundamental to natural phenomena and hold significant commercial relevance across diverse applications. While the impingement dynamics of conventional aqueous droplets on solid substrates are well-characterized, the behavior of non-aqueous droplets, particularly those influenced by external force fields like electric or magnetic fields, remains a less explored domain. This study addresses this gap by investigating the impact of a magnetic field on th…

Advanced Modeling for Exoplanet Detection and Characterization
Krishna Chamarthy
https://arxiv.org/abs/2506.17665 https://arxiv.org/p…

Advanced Modeling for Exoplanet Detection and Characterization
Research into light curves from stars (temporal variation of brightness) has completely changed how exoplanets are discovered or characterised. This study including star light curves from the Kepler dataset as a way to discover exoplanets (planetary transits) and derive some estimate of their physical characteristics by the light curve and machine learning methods. The dataset consists of measured flux (recordings) for many individual stars and we will examine the light curve of each star and l…

MGPRL: Distributed Multi-Gaussian Processes for Wi-Fi-based Multi-Robot Relative Localization in Large Indoor Environments
Sai Krishna Ghanta, Ramviyas Parasuraman
https://arxiv.org/abs/2506.23514

MGPRL: Distributed Multi-Gaussian Processes for Wi-Fi-based Multi-Robot Relative Localization in Large Indoor Environments
Relative localization is a crucial capability for multi-robot systems operating in GPS-denied environments. Existing approaches for multi-robot relative localization often depend on costly or short-range sensors like cameras and LiDARs. Consequently, these approaches face challenges such as high computational overhead (e.g., map merging) and difficulties in disjoint environments. To address this limitation, this paper introduces MGPRL, a novel distributed framework for multi-robot relative loca…

Veracity: An Open-Source AI Fact-Checking System
Taylor Lynn Curtis, Maximilian Puelma Touzel, William Garneau, Manon Gruaz, Mike Pinder, Li Wei Wang, Sukanya Krishna, Luda Cohen, Jean-Fran\c{c}ois Godbout, Reihaneh Rabbany, Kellin Pelrine
https://arxiv.org/abs/2506.15794

Veracity: An Open-Source AI Fact-Checking System
The proliferation of misinformation poses a significant threat to society, exacerbated by the capabilities of generative AI. This demo paper introduces Veracity, an open-source AI system designed to empower individuals to combat misinformation through transparent and accessible fact-checking. Veracity leverages the synergy between Large Language Models (LLMs) and web retrieval agents to analyze user-submitted claims and provide grounded veracity assessments with intuitive explanations. Key feat…

First day of #school. 👨‍🎓📚
Today at Udupi Krishna Matha: The Puthige Swamiji teaching the school year's first class to students of Puthige Suguna School, #Udupi.
#education #gurukula #Vedic #India