Searcharxiv⌕ Search

arXiv subjects

Amit Agarwal

Publications and source records attributed to Amit Agarwal.

At least 19 recordsLinked to original sources
arXiv2026

Extrinsic orbital Edelstein effect from asymmetric scattering

The generation and manipulation of orbital angular momentum (OAM) by an external electric field constitute one of the central themes of orbitronics. In particular, the electrically induced nonequilibrium OAM polarization, known as the orbital Edelstein effect (OEE), has attracted considerable attention in recent years. While the intrinsic band-geometric mechanism and the role of conventional symmetric impurity scattering in the OEE are well understood, the contribution from disorder-induced asymmetric scattering remains unclear. Here, we develop a semiclassical theory that separates the OEE into intrinsic, Drude, side-jump, and third- and fourth-order skew-scattering channels. Unlike the Drude channel, the intrinsic, side-jump, and skew-scattering responses survive only in systems with broken time-reversal symmetry. We find that in a magnetized Rashba two-dimensional electron gas (2DEG), these disorder-induced mechanisms can substantially exceed the intrinsic contribution. Remarkably, we find that for a system with Rashba coupling of $1$ $eV \AA$, the orbital magnetization is about one order of magnitude larger than the spin magnetization for the chosen parameters, highlighting the crucial role of orbital degrees of freedom in the Edelstein effect.

cond-mat.mes-hall↗
arXiv2026

Knowing When Not to Answer: Abstention and Refusal Reasoning in Vision--Language Models

Many medical conditions require diagnosis through detailed, multi-context clinical assessment rather than from visual appearance alone. Despite this, vision-language models (VLMs) are increasingly queried to interpret images in ways that touch on medical or diagnostic judgments, raising safety concerns when such inferences are unsupported. ASD diagnosis requires behavioral and developmental evidence, not static facial photographs. We audit whether VLMs abstain from this unanswerable paired-image query, and whether expressions sway non-abstaining choices. We introduce PARITY (Paired Assessment with Reused Identity), a synthetic, demographically balanced set of identity-controlled neutral/expression portrait pairs with neutral-neutral controls. All identities are synthetic and have no ASD status; because the query is unanswerable from images, any non-abstaining selection is treated as a harmful attribution. Across contemporary VLMs, we find a clear split between refusal-first models and speculative models; in the latter, certain expressions disproportionately trigger harmful selections. Clinical guardrails and single-image framing substantially increase abstention, suggesting actionable mitigations in both prompting and interface design

cs.CV↗
arXiv2026

HBQ: Hierarchical Scaling Block Quantization with Hardware-Efficiency-Aware Design for Accurate LLM Inference

Block Quantization (BQ) is a promising approach for efficient deployment of large language models (LLMs), enabling low-precision computation with controlled accuracy degradation. Compared to scalar weight-only quantization (WoQ), BQ quantizes both weight and activation, offering higher hardware efficiency and end-to-end inference on a unified datapath, but its design space, spanning bit-width, block size, scaling, and numeric formats, remains underexplored. We provide hardware/benchmark results through design space exploration (DSE). We find that increasing block size improves hardware efficiency by amortizing dequantization and accumulation costs, but degrades accuracy. This trade-off limits conventional BQ methods. Motivated by this insight, we propose Hierarchical Block Quantization (HBQ). Unlike prior methods [1], [2], which use small blocks and conventional Power-of-Two (PoT) or integer-based scaling, HBQ uses large blocks to maximize efficiency and introduces low-overhead significand (SIG) scaling for second-level quantization. By allocating quantization levels effectively and accounting for distinct activation and weight distributions, SIG scaling compensates for large-block errors more effectively than prior PoT and INT schemes. HBQ-A (accurate) achieves W4A16-level accuracy using only W4A5 while requiring less silicon area than NVFP4. HBQ-E (efficient) further reduces hardware cost by 17% while maintaining higher accuracy than all existing BQ methods. We implemented a 28nm ASIC accelerator applying HBQ to weights, activations, and KV cache, and integrated a novel partial-sum BQ scheme to further reduce EMA energy. Compared to state-of-the-art WoQ, HBQ delivers $2.3\times$/$4.6\times$ higher area/energy efficiency at the same accuracy level; $1.6$--$3.3\times$ system energy reduction and $1.5$--$3.0\times$ speedup over prior BQ methods while providing best accuracy.

cs.LG↗
arXiv2026

Quantum oscillation spectroscopy of Fermi-surface topologies in tetralayer graphene

Quantum oscillations offer a direct probe of Fermi-surface topology and electronic degeneracy, yet disentangling both simultaneously across the Lifshitz transitions of multiband systems has remained an open experimental challenge. Here, we use Shubnikov-de Haas spectroscopy on a high-mobility, dual-gated Bernal-stacked tetralayer graphene (B-4LG) device to quantitatively reconstruct the complete sequence of six distinct Fermi-surface topologies-gully, annular, singly connected, and multiband pockets. The extracted oscillation frequencies determine the extremal momentum-space areas and their spin, valley, and gully-resolved degeneracies, in quantitative agreement with our tight-binding calculations. We further show that a perpendicular magnetic-field, combined with displacement-field lifts the valley degeneracy through an orbital-Zeeman coupling, producing a single-particle valley splitting of several $meV$, far larger than in bilayer or trilayer graphene. Our work demonstrates a framework for tracking Fermi-surface topologies and their flavor degeneracies in multiband quantum materials.

cond-mat.mes-hall↗
arXiv2026

Diagnosing the origin of quantum oscillation beating in graphene

Magnetic quantum oscillations are usually periodic in inverse magnetic field, and their amplitude can show beating when two nearby frequencies interfere. In graphene-based hexagonal systems, such beating can arise from strain-induced pseudomagnetic fields, unequal valley populations, valley-dependent energy shifts, spin-orbit coupling-induced band splitting, or Kekul\'e distortions. Here, we show that the carrier density and magnetic field dependence of the beating nodes can distinguish these mechanisms. Starting from Onsager's quantization relation, we derive scaling relations for the critical carrier density $N_c$ for the beating nodes as a function of critical magnetic field $B_c$. A pseudomagnetic field gives $N_c\propto B_c^2$, whereas a density-independent valley imbalance gives $N_c\propto B_c$. A constant Dirac-band energy splitting by Zeeman-like spin-orbit coupling also gives quadratic field scaling, but with a different node sequence: $N_{c,j}\propto(2j+1)B_{c,j}^2$ for a pseudomagnetic field and $N_{c,j}\propto(2j+1)^2B_{c,j}^2$ for energy splitting, where $j$ labels the beating node indices. These results provide quantitative constraints on different microscopic origins of valley- and spin-dependent band splittings in graphene-based systems.

cond-mat.mes-hall↗
arXiv2026

Planar Hall effect in single and bilayer Rashba systems

The planar Hall effect (PHE) is an anisotropic magnetotransport response generated by coplanar electric and magnetic fields. We investigate the PHE in single- and bilayer two-dimensional electron gases (2DEGs) with Rashba spin-orbit coupling and identify two distinct mechanisms: Zeeman coupling and a band geometric channel. In the Zeeman channel, an in-plane magnetic field distorts the Rashba spin-orbit-coupled band dispersion and generates anisotropic carrier velocities, producing a finite PHE. In an asymmetric Rashba bilayer, interlayer electronic delocalization generates finite planar Berry curvature and orbital magnetic moment components, giving rise to a band geometric PHE channel. Using semiclassical Boltzmann transport theory, we calculate the chemical potential and angular dependence of the planar Hall conductivity for both mechanisms. Symmetry analysis shows that the leading response is quadratic in the magnetic field and exhibits the characteristic $\pi$-periodic angular dependence. For the parameter regime considered here, the Zeeman-induced contribution dominates, while the band geometric channel provides a distinct symmetry-allowed contribution unique to asymmetric Rashba bilayers. Our results reveal microscopic origins of anisotropic magnetotransport in spin-orbit-coupled two-dimensional materials.

cond-mat.mes-hall↗
arXiv2026

Do Image-Text Metrics Respect Semantic Invariances?

Reference-free image-to-text evaluators are now standard for scoring image-caption alignment, yet it is unclear whether they respect semantic invariances. We present an invariance probe on five popular evaluators (CLIPScore, PAC-S, UMIC, FLEUR, and a deterministic LLM judge) under semantics-preserving perturbations along three axes -- spatial (flips, context-preserving repositioning, light rotations), object (scale, category), and socio-linguistic framing (cultural/economic adjectives with neutral and length-matched controls). Across curated slices of three detection datasets and three caption evaluation suites, we find consistent non-semantic sensitivities, where benign spatial edits and simple phrasing changes shift scores by $\approx$6--9\% on average, and for systems separated by just 0.7\%, these shifts can cause ranking flips in up to $\sim$37\% of cases, particularly under spatial changes. A small human study also supports this finding and confirms that annotators generally judge perturbed pairs as equally correct, so these shifts reflect metric behavior rather than semantic change. We further propose invariance-calibrated scoring, a post-hoc adjustment that roughly halves median absolute sensitivity while retaining correlation with learned caption evaluators.

cs.CV↗
arXiv2026

Quantum-metric Bloch oscillations in weakly inhomogeneous electric fields

Geometric analogs of Bloch oscillations studied so far have relied on Berry curvature. We show that a weakly inhomogeneous electric field adds a distinct quantum-metric term to semiclassical wavepacket dynamics, generating an oscillatory real-space contribution even when the Berry curvature vanishes. The associated transport response comprises an intrinsic and a scattering-time-dependent part. In the regime studied, the latter can dominate and approach finite saturation at high field when the relative field inhomogeneity is held fixed. A tilted Dirac model illustrates the mechanism. Realistic platforms will likely require synthetically engineered superlattices, with a finite quantum metric and an adequate band gap.

cond-mat.mes-hall↗
arXiv2026

GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations

Benchmarks like GSM8K are popular measures of mathematical reasoning, but leaderboard gains can overstate true capability due to memorization of fixed test sets. Most robustness variants apply surface-level perturbations (paraphrases, renamings, number swaps, distractors) that largely preserve the underlying facts, and static releases can themselves become memorization targets over time. We introduce GSM-SEM, a reusable and stochastic framework for generating semantically diverse benchmark variants with substantially higher semantic variance than prior approaches. GSM-SEM perturbs problem statements by modifying entities, attributes, and/or relationships, frequently altering underlying facts and requiring models to recompute solutions under new conditions, while constraining generation to preserve the original calculations/answer and approximate problem difficulty. GSM-SEM generates fresh variants on each run without requiring re-annotation, reducing reliance on static public benchmarks for evaluation and thereby lowering the bias of memorization. We apply GSM-SEM on GSM8K and two existing variation suites (GSM-Symbolic and GSM-Plus), producing GSM8K-SEM, GSM-Symbolic-SEM, and GSM-Plus-SEM. Evaluating 14 SOTA LLMs, we observe consistent performance drops with larger decline when semantic perturbations are coupled with symbolic/plus variations (average drop rate 28% in maximum strictness configuration of GSM-SEM). We publicly release the three SEM variants as fully human-validated datasets. Finally, to demonstrate applicability beyond GSM-style math problems, we apply GSM-SEM to additional benchmarks including BigBenchHard, LogicBench, and NLR-BIRD.

cs.CL↗
arXiv2026

Orbital-Splitter Current in Altermagnets

In collinear altermagnets, the real-space rotational symmetry of opposite spin sublattices generates a large nonrelativistic spin-splitter current. Orbital transport in this setting has remained largely unexplored. Here, we introduce the orbital-splitter current (OSC), an orbital analogue of the spin-splitter current, and derive its Drude and orbital Berry curvature contributions using a density-matrix framework. We show that the $d$-wave altermagnet $\mathrm{FeSb}_2$ realizes a purely intrinsic OSC because mirror symmetries suppress the Drude channel by forcing the orbital magnetic moment to vanish. The OSC response is strongly anisotropic and, for selected field orientations, exceeds the spin-splitter current by nearly a factor of four. We further show that the OSC generates a damping-like torque in an altermagnet-ferromagnet heterostructure and, when combined with the spin-splitter current, significantly reduces the magnetization switching time.

cond-mat.mes-hall↗
arXiv2026

Robust Audio-Text Retrieval via Cross-Modal Attention and Hybrid Loss

Audio-text retrieval enables semantic alignment between audio content and natural language queries, supporting applications in multimedia search, accessibility, and surveillance. However, current state-of-the-art approaches struggle with long, noisy, and weakly labeled audio due to their reliance on contrastive learning and large-batch training. We propose a novel multimodal retrieval framework that refines audio and text embeddings using a cross-modal embedding refinement module combining transformer-based projection, linear mapping, and bidirectional attention. To further improve robustness, we introduce a hybrid loss function blending cosine similarity, $\mathcal{L}_{1}$, and contrastive objectives, enabling stable training even under small-batch constraints. Our approach efficiently handles long-form and noisy audio (SNR 5 to 15) via silence-aware chunking and attention-based pooling. Experiments on benchmark datasets demonstrate improvements over prior methods.

cs.CL↗
arXiv2026

Intrinsic Magnetoelectric Hall Effect from Layer-Orbital Quantum Geometry

Intrinsic Hall effects, such as the anomalous Hall effect, originate from the orbital quantum geometry of Bloch states. However, in layered materials, the combined action of out-of-plane electric and magnetic fields couples to layer polarization and orbital moment, generating a mixed layer-orbital quantum geometry in field-dressed Bloch states. We show that this geometry produces an intrinsic magnetoelectric Hall effect that is bilinear in the electric and magnetic fields. The response is scattering-time independent and can arise in nonmagnetic systems without spin-orbit coupling. Its origin lies in interband coherence involving layer polarization and orbital moment, leading to a finite, non-quantized Hall response that persists in the band gap. The Hall coefficient is odd under gate reversal and tracks layer polarization. A symmetry analysis identifies the classes of layered materials that host this effect. As a representative realization, we demonstrate the effect in rhombohedral pentalayer graphene, where the conductivity reaches values of order $0.05\,e^2/h$. These results establish mixed layer-orbital quantum geometry as a mechanism for intrinsic magnetoelectric Hall transport and a direct probe of layer-resolved quantum geometry in Bloch bands.

cond-mat.mes-hall↗
arXiv2026

Asymmetric Scattering-Induced Neel Spin-Orbit Torque in Antiferromagnets

Magnetic switching in antiferromagnets relies on Neel spin orbit torque (NSOT), which originates from a current-induced staggered spin polarization of itinerant electrons. In collinear antiferromagnets, such a response requires the spin susceptibility to be odd under combined space-time inversion symmetry (PT), and is conventionally attributed to symmetric scattering processes. Here, we demonstrate that asymmetric impurity scattering generates an additional PT-odd spin polarization when coupled with the anomalous spin polarizability (ASP) of Bloch electrons. This extrinsic contribution arises from the interplay between antisymmetric higher-order scattering processes and band geometry, effectively converting an otherwise PT-even susceptibility into a staggered spin polarization. Using a minimal model of tetragonal CuMnAs, we show that this anomalous skew-scattering contribution can be comparable to, and with sufficient impurity density even exceed, the conventional symmetric scattering (Drude) contribution. Our results identify a new band-geometry-driven mechanism for NSOT and establish an efficient route for electrical control of antiferromagnets.

cond-mat.mes-hall↗
arXiv2026

Anthropogenic Regional Adaptation in Multimodal Vision-Language Model

While the field of vision-language (VL) has achieved remarkable success in integrating visual and textual information across multiple languages and domains, there is still no dedicated framework for assessing human-centric alignment in vision-language systems. We offer two contributions to address this gap. First, we introduce Anthropogenic Regional Adaptation: a novel paradigm that aims to optimize model relevance to specific regional contexts while ensuring the retention of global generalization capabilities. Second, we present a simple, but effective adaptation method named Geographical-generalization-made-easy (GG-EZ), which utilizes regional data filtering and model merging. Through comprehensive experiments on 3 VL architectures: large vision-language models, text-to-image diffusion models, and vision-language embedding models, and a case study in Southeast Asia (SEA) regional adaptation, we demonstrate the importance of Anthropogenic Regional Adaptation and the effectiveness of GG-EZ, showing 5-15% gains in cultural relevance metrics across SEA while maintaining over 98% of global performance and even occasionally surpassing it. Our findings establish Anthropogenic Regional Alignment as a foundational paradigm towards applicability of multimodal vision-language models in diverse regions and demonstrate a simple-yet-effective baseline method that optimizes regional value alignment while preserving global generalization.

cs.AI↗
arXiv2026

Correlation-Driven Orbital Order Realizes 2D Metallic Altermagnetism

Two-dimensional metallic altermagnets are rare, and no correlated 2D material has been established to host large nonrelativistic spin splitting. Here we show that spontaneous orbital order, driven by electronic correlations and Fermi surface nesting, provides a general microscopic route to two-dimensional metallic altermagnetism. Antiferro-orbital ordering between the d$_{xz}$ and d$_{yz}$ orbitals breaks the equivalence of magnetic sublattices with opposite spins and generates a symmetry-enforced altermagnetic spin texture. As a concrete realization, we identify monolayer YbMn$_2$Ge$_2$ as a stable correlated metallic altermagnet exhibiting giant nonrelativistic spin splitting of order 1 eV. The resulting phase supports an exceptionally large and gate-tunable transverse spin conductivity. These results establish correlation-driven orbital order as a robust and general mechanism for designing correlated altermagnets with large spin splitting.

cond-mat.mes-hall↗
arXiv2026

Longitudinal Nonreciprocal Charge Transport with Time Reversal Symmetry

Longitudinal nonreciprocal charge transport is usually associated with broken time-reversal symmetry, either from magnetic order or an external magnetic field. Here, we show that it can also arise in nonmagnetic conductors preserving time-reversal symmetry through disorder-induced asymmetric scattering. Within a semiclassical Boltzmann theory, skew-scattering and side-jump processes generate a finite longitudinal current quadratic in the electric field. Our symmetry analysis identifies 42 point groups that allow this longitudinal nonreciprocal response. As a concrete example, gated Bernal-stacked bilayer graphene shows a gate-tunable nonreciprocal response with clear enhancement near its Lifshitz transition. These results identify disorder-driven asymmetric scattering as a route to bulk longitudinal nonreciprocal charge transport in crystalline conductors.

cond-mat.mes-hall↗
arXiv2026

Think Twice Before You Write -- an Entropy-based Decoding Strategy to Enhance LLM Reasoning

Decoding strategies play a central role in shaping the reasoning ability of large language models (LLMs). Traditional methods such as greedy decoding and beam search often suffer from error propagation, while sampling-based approaches introduce randomness without adequate robustness. Self-consistency improves reliability by aggregating multiple rollouts, but incurs significant computational overhead. We propose an entropy-guided decoding framework that introduces token-level adaptivity into generation. At each step, the model computes the entropy of the token distribution, identifies high-uncertainty positions, and selectively branches on these vulnerable points. A dynamic pool of partial rollouts is maintained and expanded until solutions are completed, concentrating computation where uncertainty is greatest and avoiding unnecessary exploration in confident regions. To enable efficient termination, we apply a rollout-level Entropy After (EAT) stopping criterion by performing entropy evaluation after the full reasoning trace, rather than incrementally at every step. Experiments on GSM8K, AMC2023, and their perturbed variants demonstrate that our method achieves consistently strong accuracy. Notably, on smaller LLMs, performance is comparable to GPT-5 while operating at a fraction of the cost.

cs.CL↗
arXiv2026

Electric-Polarization Probe of the Magnon Orbital Moment Current in Altermagnet

Efficient transport of spin and orbital moments, and their electrical detection, are among the main challenges in spintronics and orbitronics. In magnetic insulators, these currents are mediated by magnons. In addition to carrying spin and orbital moment, the orbital motion of a magnon combined with its magnetic moment, generates an effective electric dipole moment. Here, we develop a theoretical framework for Seebeck- and Nernst-type transport of the magnon orbital moment (MOM) and its associated electric dipole moment (EDM). We identify a Drude-like scattering contribution and an intrinsic component governed by the generalized Berry curvatures of magnon bands. We show that a measurable transverse voltage generated by the EDM current provides a direct electrical detection scheme for magnon orbital transport. Applying our theory to an hexagonal altermagnet, we obtain an experimentally accessible voltage of approximately $0.4~\mu$V. Our results establish a concrete electrical probe of magnon orbital transport and highlight magnons as potential low-dissipation information carriers for orbitronics.

cond-mat.mes-hall↗