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cs.CL updates on arXiv.org

Indexing Multimodal Language Models for Large-scale Image Retrieval SpatialEvo: Self-Evolving Spatial Intelligence via Deterministic Geometric Environments PersonaVLM: Long-Term Personalized Multimodal LLMs MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imaging Who Gets Flagged? The Pluralistic Evaluation Gap in AI Content Watermarking VLMs Need Words: Vision Language Models Ignore Visual Detail In Favor of Semantic Anchors (How) Learning Rates Regulate Catastrophic Overtraining Parameter Importance is Not Static: Evolving Parameter Isolation for Supervised Fine-Tuning $π$-Play: Multi-Agent Self-Play via Privileged Self-Distillation without External Data A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection The Consciousness Cluster: Emergent preferences of Models that Claim to be Conscious KMMMU: Evaluation of Massive Multi-discipline Multimodal Understanding in Korean Language and Context Dental-TriageBench: Benchmarking Multimodal Reasoning for Hierarchical Dental Triage Detection Without Correction: A Robust Asymmetry in Activation-Based Hallucination Probing Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size C2: Scalable Rubric-Augmented Reward Modeling from Binary Preferences Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference From $P(y|x)$ to $P(y)$: Investigating Reinforcement Learning in Pre-train Space UI-Zoomer: Uncertainty-Driven Adaptive Zoom-In for GUI Grounding Reward Design for Physical Reasoning in Vision-Language Models Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning MERRIN: A Benchmark for Multimodal Evidence Retrieval and Reasoning in Noisy Web Environments Toward Generalized Cross-Lingual Hateful Language Detection with Web-Scale Data and Ensemble LLM Annotations Self-Calibrating Language Models via Test-Time Discriminative Distillation HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation Claim2Vec: Embedding Fact-Check Claims for Multilingual Similarity and Clustering Spoiler Alert: Narrative Forecasting as a Metric for Tension in LLM Storytelling Human vs. Machine Deception: Distinguishing AI-Generated and Human-Written Fake News Using Ensemble Learning Weird Generalization is Weirdly Brittle Mirroring Minds: Asymmetric Linguistic Accommodation and Diagnostic Identity in ADHD and Autism Reddit Communities Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models Who Wrote This Line? Evaluating the Detection of LLM-Generated Classical Chinese Poetry Training-Free Cross-Lingual Dysarthria Severity Assessment via Phonological Subspace Analysis in Self-Supervised Speech Representations Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis ODUTQA-MDC: A Task for Open-Domain Underspecified Tabular QA with Multi-turn Dialogue-based Clarification Nationality encoding in language model hidden states: Probing culturally differentiated representations in persona-conditioned academic text Relational Probing: LM-to-Graph Adaptation for Financial Prediction CodeComp: Structural KV Cache Compression for Agentic Coding FAITH: Factuality Alignment through Integrating Trustworthiness and Honestness Comparative Analysis of Large Language Models in Healthcare Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation A Structured Clustering Approach for Inducing Media Narratives NameBERT: Scaling Name-Based Nationality Classification with LLM-Augmented Open Academic Data LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset BLUEmed: Retrieval-Augmented Multi-Agent Debate for Clinical Error Detection Turing or Cantor: That is the Question NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning Instruction Data Selection via Answer Divergence EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning Dynamic Adaptive Attention and Supervised Contrastive Learning: A Novel Hybrid Framework for Text Sentiment Classification Structure-Grounded Knowledge Retrieval via Code Dependencies for Multi-Step Data Reasoning Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark HeceTokenizer: A Syllable-Based Tokenization Approach for Turkish Retrieval BlasBench: An Open Benchmark for Irish Speech Recognition OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language Environment Simulation How Robust Are Large Language Models for Clinical Numeracy? An Empirical Study on Numerical Reasoning Abilities in Clinical Contexts Evaluating Memory Capability in Continuous Lifelog Scenario Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation Hidden Measurement Error in LLM Pipelines Distorts Annotation, Evaluation, and Benchmarking LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models Reproduction Beyond Benchmarks: ConstBERT and ColBERT-v2 Across Backends and Query Distributions Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution SpectralLoRA: Is Low-Frequency Structure Sufficient for LoRA Adaptation? A Spectral Analysis of Weight Updates Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference ChemPro: A Progressive Chemistry Benchmark for Large Language Models MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models PICon: A Multi-Turn Interrogation Framework for Evaluating Persona Agent Consistency CAMO: A Class-Aware Minority-Optimized Ensemble for Robust Language Model Evaluation on Imbalanced Data From Speech-to-Spatial: Grounding Utterances on A Live Shared View with Augmented Reality MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation Rethinking LLM Watermark Detection in Black-Box Settings: A Non-Intrusive Third-Party Framework Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models SODA: Semi On-Policy Black-Box Distillation for Large Language Models C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts Evaluating Cooperation in LLM Social Groups through Elected Leadership A Triadic Suffix Tokenization Scheme for Numerical Reasoning Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Anthropogenic Regional Adaptation in Multimodal Vision-Language Model METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Towards Proactive Information Probing: Customer Service Chatbots Harvesting Value from Conversation A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities Linear Representations of Hierarchical Concepts in Language Models TInR: Exploring Tool-Internalized Reasoning in Large Language Models Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models LLMs Should Incorporate Explicit Mechanisms for Human Empathy ReFEree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning The Amazing Agent Race: Strong Tool Users, Weak Navigators Think in Sentences: Explicit Sentence Boundaries Enhance Language Model's Capabilities CircuitSynth: Reliable Synthetic Data Generation ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models
EffGen: Enabling Small Language Models as Capable Autonomous Agents
Gaurav Srivastava, Aafiya Hussain, Chi Wang, Yingyan Celine Lin, · 2026-02-01 · via cs.CL updates on arXiv.org

Most existing language model agentic systems today are built and optimized for large language models (e.g., GPT, Claude, Gemini) via API calls. While powerful, this approach faces several limitations including high token costs and privacy concerns for sensitive applications. We introduce effGen, an open-source agentic framework optimized for small language models (SLMs) that enables effective, efficient, and secure local deployment (pip install effgen). effGen makes four major contributions: (1) Enhanced tool-calling with prompt optimization that compresses contexts by 70-80% while preserving task semantics, (2) Intelligent task decomposition that breaks complex queries into parallel or sequential subtasks based on dependencies, (3) Complexity-based routing using five factors to make smart pre-execution decisions, and (4) Unified memory system combining short-term, long-term, and vector-based storage. Additionally, effGen unifies multiple agent protocols (MCP, A2A, ACP) for cross-protocol communication. Results on 13 benchmarks show effGen outperforms LangChain, AutoGen, and Smolagents with higher success rates, faster execution, and lower memory. Our results reveal that prompt optimization and complexity routing have complementary scaling behavior: optimization benefits SLMs more (11.2% gain at 1.5B vs 2.4% at 32B), while routing benefits large models more (3.6% at 1.5B vs 7.9% at 32B), providing consistent gains across all scales when combined. effGen (https://effgen.org/) is released under the MIT License, ensuring broad accessibility for research and commercial use. Our framework code is publicly available at https://github.com/ctrl-gaurav/effGen.

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