activity
20242026
collaborators

13 papers

cs.RO2026

PACE: Persona Adaptation through Conversational Elicitation in Human-Robot Interaction

Peizhen Li, Longbing Cao, Megani Rajendran +3

Equipping humanoid robots with coherent and adaptable personas is crucial for fostering natural, engaging, and trustworthy human-robot interaction (HRI). However, existing approach…

cs.LG2026

FORGE: Fused On-Register Gradient Elimination for Memory-Efficient LLM Training

Dikshant Kukreja, Kritarth Prasad, Avinash Anand +6

Reverse-mode differentiation computes every weight gradient, writes it to memory, and only then lets the optimizer read it back. This two-phase schedule sets the memory ceiling of…

cs.CL2026

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes

Avinash Anand, Mahisha Ramesh, Avni Mittal +8

Reasoning has become central to how Large Language Models (LLMs) are evaluated and interpreted, spanning Chain-of-Thought (CoT), mathematical problem-solving, multi-hop question an…

cs.CL2026

IRIS: Interleaved Reinforcement with Incremental Staged Curriculum for Cross-Lingual Mathematical Reasoning

Navya Gupta, Rishitej Reddy Vyalla, Avinash Anand +8

Curriculum learning helps language models tackle complex reasoning by gradually increasing task difficulty. However, it often fails to generate consistent step-by-step reasoning, e…

cs.CL2026

Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size

Dikshant Kukreja, Kshitij Sah, Gautam Gupta +5

Larger language models become simultaneously better and worse at handling contextual information -- better at ignoring false claims, worse at ignoring irrelevant tokens. We formali…

cs.SD2026

DAST: A Dual-Stream Voice Anonymization Attacker with Staged Training

Ridwan Arefeen, Xiaoxiao Miao, Rong Tong +3

Voice anonymization masks vocal traits while preserving linguistic content, which may still leak speaker-specific patterns. To assess and strengthen privacy evaluation, we propose…